人工智能深度学习 第五期（高薪就业班）
├─10_图神经网络实战
│&nBSp;&nBSp;├─1_图神经网络基础
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-图神经网络应用领域分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-图基本模块定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-邻接矩阵的定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-GNN中常见任务.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-消息传递计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-多层GCN的作用.mp4.mp4
│&nBSp;&nBSp;├─2_图卷积GCN模型
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-GCN基本模型概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-图卷积的基本计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-邻接的矩阵的变换.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-GCN变换原理解读.mp4.mp4
│&nBSp;&nBSp;├─3_图模型必备神器PyTorch Geometric安装与使用
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-PyTorch Geometric工具包安装与配置方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据集与邻接矩阵格式.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-模型定义与训练方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-文献引用数据集分类案例实战.mp4.mp4
│&nBSp;&nBSp;├─4_使用PyTorch Geometric构建自己的图数据集
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-构建数据集基本方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据集与任务背景概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-数据集基本预处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-用户行为图结构创建.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-数据集创建函数介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-网络结构定义模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-TOPkPooling进行下采样任务.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-获取全局特征.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-模型训练与总结.mp4.mp4
│&nBSp;&nBSp;├─5_图注意力机制与序列图模型
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-图注意力机制的作用与方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-邻接矩阵计算图Attention.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-序列图神经网络TGCN应用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-序列图神经网络细节.mp4.mp4
│&nBSp;&nBSp;├─6_图相似度论文解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-要完成的任务分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-基本方法概述解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-图模型提取全局与局部特征.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-NTN模块的作用与效果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-点之间的对应关系计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-结果输出与总结.mp4.mp4
│&nBSp;&nBSp;├─7_图相似度计算实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与任务概述3.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-图卷积特征提取模块3.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-分别计算不同Batch点的分布3.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-获得直方图特征结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-图的全局特征构建.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-NTN图相似特征提取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-预测得到相似度结果.mp4.mp4
│&nBSp;&nBSp;├─8_基于图模型的轨迹估计
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与标注信息解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-整体三大模块分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-特征工程的作用与效果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-传统方法与现在向量空间对比.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-输入细节分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-子图模块构建方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-特征融合模块分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-VectorNet输出层分析.mp4.mp4
│&nBSp;&nBSp;└─9_图模型轨迹估计实战
│&nBSp;&nBSp;└─├┈1-数据与环境配置4.mp4.mp4
│&nBSp;&nBSp;└─├┈2-训练数据准备4.mp4.mp4
│&nBSp;&nBSp;└─├┈3-Agent特征提取方法4.mp4.mp4
│&nBSp;&nBSp;└─├┈4-DataLoADer构建图结构4.mp4.mp4
│&nBSp;&nBSp;└─└┈5-SubGraph与Attention模型流程4.mp4.mp4
├─1_直播课回放
│&nBSp;&nBSp;├─1_直播1：开班典礼
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈1人工智能CV NLP高薪实战班.mp4
│&nBSp;&nBSp;├─2_Pycharm环境配置与Debug演示(没用过的同学必看)
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈Pycharm环境配置与Debug演示(没用过的同学必看).mp4
│&nBSp;&nBSp;├─3_直播2：深度学习必备基础-神经网络与卷积网络
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈1.深度学习必备基础-神经网络与卷积网络.mp4
│&nBSp;&nBSp;├─4_直播3：Transformer原理及其各领域应用分析
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈Transformer原理及其各领域应用分析.mp4
│&nBSp;&nBSp;├─5_额外补充：时间序列预测
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈额外补充：时间序列预测.mp4
│&nBSp;&nBSp;└─6_直播4：Informer时间序列预测源码解读
│&nBSp;&nBSp;└─└┈Informer时间序列预测源码解读.mp4
├─2_深度学习必备核心算法
│&nBSp;&nBSp;├─1_神经网络算法解读
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈1-神经网络算法解读.mp4
│&nBSp;&nBSp;├─2_卷积神经网络算法解读
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈2-卷积神经网络算法解读.mp4
│&nBSp;&nBSp;└─3_递归神经网络算法解读
│&nBSp;&nBSp;└─└┈3-递归神经网络算法解读.mp4
├─3_深度学习核心框架PyTorch
│&nBSp;&nBSp;├─1_PyTorch框架介绍与配置安装
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-PyTorch框架与其他框架区别分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈2-CPU与GPU版本安装方法解读1.mp4.mp4
│&nBSp;&nBSp;├─2_使用神经网络进行分类任务
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与任务概述2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-基本模块应用测试2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-网络结构定义方法2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-数据源定义简介2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-损失与训练模块分析2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-训练一个基本的分类模型2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-参数对结果的影响2.mp4.mp4
│&nBSp;&nBSp;├─3_神经网络回归任务-气温预测
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈神经网络回归任务-气温预测1.mp4.mp4
│&nBSp;&nBSp;├─4_卷积网络参数解读分析
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-输入特征通道分析2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-卷积网络参数解读2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-卷积网络模型训练2.mp4.mp4
│&nBSp;&nBSp;├─5_图像识别模型与训练策略（重点）
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-任务分析与图像数据基本处理2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-测试结果演示分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据增强模块2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-数据集与模型选择1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-迁移学习方法解读1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-输出层与梯度设置1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-输出类别个数修改1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-优化器与学习率衰减1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-模型训练方法1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-重新训练全部模型1.mp4.mp4
│&nBSp;&nBSp;├─6_DataLoADer自定义数据集制作
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-DataloADer要完成的任务分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-图像数据与标签路径处理1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-DataloADer中需要实现的方法分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-实用DataloADer加载数据并训练模型1.mp4.mp4
│&nBSp;&nBSp;├─7_LSTM文本分类实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与任务目标分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-文本数据处理基本流程分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-命令行参数与DEBUG1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-训练模型所需基本配置参数分析1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-预料表与字符切分1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-字符预处理转换ID1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-LSTM网络结构基本定义1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-网络模型预测结果输出1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-模型训练任务与总结1.mp4.mp4
│&nBSp;&nBSp;└─8_PyTorch框架Flask部署例子
│&nBSp;&nBSp;└─├┈1-基本结构与训练好的模型加载.mp4.mp4
│&nBSp;&nBSp;└─├┈2-服务端处理与预测函数.mp4.mp4
│&nBSp;&nBSp;└─└┈3-基于Flask测试模型预测结果.mp4.mp4
├─4_MMLAB实战系列
│&nBSp;&nBSp;├─10_第四模块：DBNET文字检测
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-文字检测数据概述与配置文件.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-配置文件参数设置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-Neck层特征组合.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-损失函数模块概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-损失计算方法.mp4.mp4
│&nBSp;&nBSp;├─11_第四模块：ANINET文字识别
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与环境概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-配置文件修改方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-Bakbone模块得到特征.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-视觉Transformer模块的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-视觉模型中的编码与解码的效果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-文本模型中的结构分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-迭代修正模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-输出层与损失计算.mp4.mp4
│&nBSp;&nBSp;├─12_第四模块：KIE基于图模型的关键信息抽取
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-配置文件以及要完成的任务解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-KIE数据集格式调整方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-配置文件与标签要进行处理操作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-边框要计算的特征分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-标签数据处理与关系特征提取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-特征合并处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-准备拼接边与点特征.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-整合得到图模型输入特征.mp4.mp4
│&nBSp;&nBSp;├─12_第五模块：styleGAN2源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-要完成的任务与基本思想概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-得到style特征编码.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-特征编码风格拼接.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-基础风格特征卷积模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-上采样得到输出结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-损失函数概述.mp4.mp4
│&nBSp;&nBSp;├─13_第六模块：BasicVSR++视频超分辨重构源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-要完成的任务分析与配置文件.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-传播流程整体完成一圈.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-完成输出结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-特征基础提取模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-光流估计网络模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-基于光流完成对齐操作.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-偏移量计算方法1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-双向计算特征对齐.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-提特征传递流程分析.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-序列传播计算.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-准备变形卷积模块的输入.mp4.mp4
│&nBSp;&nBSp;├─14_第七模块：多模态3D目标检测算法源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-环境配置与数据集概述.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-3D卷积特征融合.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-输出层预测结果.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据与标注文件介绍.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-基本流程梳理并进入debug模式.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-数据与图像特征提取模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-体素索引位置获取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-体素特征提取方法解读.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-体素特征计算方法分析.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-全局体素特征提取.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-多模态特征融合.mp4
│&nBSp;&nBSp;├─15_第八模块：模型蒸馏应用实例
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-任务概述与工具使用.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-Teacher与Student网络结构定义.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-训练T与S得到蒸馏模型.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-开始模型训练过程与问题修正.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-日志输出与模型分离.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-分别得到Teacher与Student模型.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-实际测试效果演示.mp4
│&nBSp;&nBSp;├─16_第八模块：模型剪枝方法概述分析
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-SuperNet网络结构分析与剪枝概述.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈2-搜索匹配到符合计算量的模型并训练.mp4
│&nBSp;&nBSp;├─17_第九模块：mmaction行为识别
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈创建自己的行为识别标注数据集.mp4
│&nBSp;&nBSp;├─18_额外补充
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈在源码中加入各种注意力机制方法.mp4
│&nBSp;&nBSp;├─1_MMCV安装方法
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈MMCV安装方法.mp4
│&nBSp;&nBSp;├─2_第一模块：分类任务基本操作
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-准备MMCLS项目.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-基本参数配置解读.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-各模块配置文件组成.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-生成完整配置文件.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-根据文件夹定义数据集.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-构建自己的数据集.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-训练自己的任务.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈MMCLS问题修正1.mp4
│&nBSp;&nBSp;├─3_第一模块：训练结果测试与验证
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-测试DEMO效果.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-测试评估模型效果.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-MMCLS中增加一个新的模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-修改配置文件中的参数.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-数据增强流程可视化展示.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-GrAD-CAM可视化方法.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-可视化细节与效果分析.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-MMCLS可视化模块应用.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-模型分析脚本使用.mp4
│&nBSp;&nBSp;├─4_第一模块：模型源码DEBUG演示
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-VIT任务概述.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据增强模块概述分析.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-PatchEmbedding层.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-前向传播基本模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-CLS与输出模块.mp4
│&nBSp;&nBSp;├─5_第二模块：使用分割模块训练自己的数据集
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-项目配置基本介绍.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据集标注与制作方法.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-跟别预测类别数修改配置文件.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-加载预训练模型开始训练.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-预测DEMO演示.mp4
│&nBSp;&nBSp;├─6_第二模块：基于Unet进行各种策略修改
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-配置文件解读.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-编码层模块.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-上采样与输出层.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-辅助层的作用.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-给Unet添加一个neck层.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-如何修改参数适配网络结构.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-将Unet特征提取模块替换成transformer.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-VIT模块源码分析.mp4
│&nBSp;&nBSp;├─7_第二模块：分割任务CVPr最新Backbone设计及其应用
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-注册自己的Backbone模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-汇总多层级特征进行输出.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-配置文件指定.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-DEBUG解读Backbone设计.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-PatchEmbedding的作用与实现.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-卷积位置编码计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-近似Attention模块实现.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-完成特征提取与融合模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-分割任务输出模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-全局特征的作用与实现.mp4.mp4
│&nBSp;&nBSp;├─8_第三模块：mmdet训练自己的数据任务
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集标注与标签获取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-COCO数据标注格式.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-通过脚本生成COCO数据格式.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-配置文件数据增强策略分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-训练所需配置说明.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-模型训练与DEMO演示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-模型测试与可视化分析模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-补充：评估指标.mp4.mp4
│&nBSp;&nBSp;└─9_第三模块：DeformableDetr物体检测源码分析
│&nBSp;&nBSp;└─├┈1-特征提取与位置编码.mp4
│&nBSp;&nBSp;└─├┈10-分类与回归输出模块.mp4
│&nBSp;&nBSp;└─├┈11-预测输出结果与标签匹配模块.mp4
│&nBSp;&nBSp;└─├┈2-序列特征展开并叠加.mp4
│&nBSp;&nBSp;└─├┈3-得到相对位置点编码.mp4
│&nBSp;&nBSp;└─├┈4-准备Encoder编码层所需全部输入.mp4
│&nBSp;&nBSp;└─├┈5-编码层中的序列分析.mp4
│&nBSp;&nBSp;└─├┈6-偏移量offset计算.mp4
│&nBSp;&nBSp;└─├┈7-偏移量对齐操作.mp4
│&nBSp;&nBSp;└─├┈8-Encoder层完成特征对齐.mp4
│&nBSp;&nBSp;└─└┈9-Decoder要完成的操作.mp4
├─5_Opencv图像处理框架实战
│&nBSp;&nBSp;├─10_项目实战-文档扫描OCR识别
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-整体流程演示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-文档轮廓提取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-原始与变换坐标计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-透视变换结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-tesseract-OCR安装配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-文档扫描识别效果.mp4.mp4
│&nBSp;&nBSp;├─11_图像特征-harris
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-角点检测基本原理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-基本数学原理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-求解化简.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-特征归属划分.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-opencv角点检测效果.mp4.mp4
│&nBSp;&nBSp;├─12_图像特征-sift
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-尺度空间定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-高斯差分金字塔.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-特征关键点定位.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-生成特征描述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-特征向量生成.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-opencv中sift函数使用.mp4.mp4
│&nBSp;&nBSp;├─13_案例实战-全景图像拼接
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-特征匹配方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-RANSAC算法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-图像拼接方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-流程解读.mp4.mp4
│&nBSp;&nBSp;├─14_项目实战-停车场车位识别
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-任务整体流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-所需数据介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-图像数据预处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-车位直线检测.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-按列划分区域.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-车位区域划分.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-识别模型构建.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-基于视频的车位检测.mp4.mp4
│&nBSp;&nBSp;├─15_项目实战-答题卡识别判卷
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-整体流程与效果概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-预处理操作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-填涂轮廓检测.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-选项判断识别.mp4.mp4
│&nBSp;&nBSp;├─16_背景建模
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-背景消除-帧差法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-混合高斯模型.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-学习步骤.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-背景建模实战.mp4.mp4
│&nBSp;&nBSp;├─17_光流估计
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-基本概念.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-Lucas-KanADe算法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-推导求解.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-光流估计实战.mp4.mp4
│&nBSp;&nBSp;├─18_Opencv的DNN模块
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-dnn模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈2-模型加载结果输出.mp4.mp4
│&nBSp;&nBSp;├─19_项目实战-目标追踪
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-目标追踪概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-多目标追踪实战.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-深度学习检测框架加载.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-基于dlib与sSD的追踪.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-多进程目标追踪.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-多进程效率提升对比.mp4.mp4
│&nBSp;&nBSp;├─1_课程简介与环境配置
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈0-课程简介2.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-Notebook与IDE环境.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈2-python与Opencv配置安装.mp4.mp4
│&nBSp;&nBSp;├─20_卷积原理与操作
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-卷积神经网络的应用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-卷积效果演示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-卷积操作流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-卷积层解释.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-卷积计算过程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-pADing与stride.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-卷积参数共享.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-池化层原理.mp4.mp4
│&nBSp;&nBSp;├─21_项目实战-疲劳检测
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-关键点定位概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-获取人脸关键点.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-定位效果演示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-闭眼检测.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-检测效果.mp4.mp4
│&nBSp;&nBSp;├─2_图像基本操作
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-计算机眼中的图像.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-视频的读取与处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-ROI区域.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-边界填充.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-数值计算.mp4.mp4
│&nBSp;&nBSp;├─3_阈值与平滑处理
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-图像平滑处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-高斯与中值滤波.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈图像阈值.mp4.mp4
│&nBSp;&nBSp;├─4_图像形态学操作
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-腐蚀操作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-膨胀操作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-开运算与闭运算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-梯度计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-礼帽与黑帽.mp4.mp4
│&nBSp;&nBSp;├─5_图像梯度计算
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Sobel算子.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-梯度计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-scharr与lapkacian算子.mp4.mp4
│&nBSp;&nBSp;├─6_边缘检测
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Canny边缘检测流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-非极大值抑制.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-边缘检测效果.mp4.mp4
│&nBSp;&nBSp;├─7_图像金字塔与轮廓检测
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-轮廓检测方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-模板匹配方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-图像金字塔定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-金字塔制作方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-轮廓检测结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-匹配效果展示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-轮廓特征与近似.mp4.mp4
│&nBSp;&nBSp;├─8_直方图与傅里叶变换
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-傅里叶概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-直方图定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-均衡化原理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-频域变换结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-低通与高通滤波.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-均衡化效果.mp4.mp4
│&nBSp;&nBSp;└─9_项目实战-信用卡数字识别
│&nBSp;&nBSp;└─├┈2-环境配置与预处理.mp4.mp4
│&nBSp;&nBSp;└─├┈3-模板处理方法.mp4.mp4
│&nBSp;&nBSp;└─├┈4-输入数据处理方法.mp4.mp4
│&nBSp;&nBSp;└─├┈5-模板匹配得出识别结果.mp4.mp4
│&nBSp;&nBSp;└─└┈总体流程与方法讲解.mp4.mp4
├─6_综合项目-物体检测经典算法实战
│&nBSp;&nBSp;├─10_EfficientNet网络
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈第八课：EfficientNet网络模型.mp4.mp4
│&nBSp;&nBSp;├─11_EfficientDet检测算法
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈第十一章：EfficientDet检测算法.mp4.mp4
│&nBSp;&nBSp;├─12_基于Transformer的detr目标检测算法
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-DETR目标检测基本思想解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-整体网络架构分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-位置信息初始化query向量.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-注意力机制的作用方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-训练过程的策略.mp4.mp4
│&nBSp;&nBSp;├─13_detr目标检测源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-项目环境配置解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据处理与dataloADer.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-位置编码作用分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-backbone特征提取模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-mask与编码模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-编码层作用方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-Decoder层操作与计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-输出预测结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-损失函数与预测输出.mp4.mp4
│&nBSp;&nBSp;├─1_深度学习经典检测方法概述
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-检测任务中阶段的意义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-不同阶段算法优缺点分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-IOU指标计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-评估所需参数计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-map指标计算.mp4.mp4
│&nBSp;&nBSp;├─2_YOLO-V1整体思想与网络架构
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-检测算法要得到的结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-整体网络架构解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-位置损失计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-置信度误差与优缺点分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈YOLO算法整体思路解读.mp4.mp4
│&nBSp;&nBSp;├─3_YOLO-V2改进细节详解
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-网络结构特点.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-架构细节解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-基于聚类来选择先验框尺寸.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-偏移量计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-坐标映射与还原.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-感受野的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-特征融合改进.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈V2版本细节升级概述.mp4.mp4
│&nBSp;&nBSp;├─4_YOLO-V3核心网络模型
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-V3版本改进概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-多scale方法改进与特征融合.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-经典变换方法对比分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-残差连接方法解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-整体网络模型架构分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-先验框设计改进.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-sotfmax层改进.mp4.mp4
│&nBSp;&nBSp;├─5_项目实战-基于V3版本进行源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据与环境配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-网格偏移计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-模型要计算的损失概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈12-标签值格式修改.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈13-坐标相对位置计算.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈14-完成所有损失函数所需计算指标.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈15-模型训练与总结.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈16-预测效果展示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-训练参数设置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-数据与标签读取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-标签文件读取与处理.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-debug模式介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-基于配置文件构建网络模型.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-路由层与shortcut层的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-YOLO层定义解析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-预测结果计算.mp4.mp4
│&nBSp;&nBSp;├─6_基于YOLO-V3训练自己的数据集与任务
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Labelme工具安装.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据信息标注.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-完成标签制作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-生成模型所需配置文件.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-json格式转换成yolo-V3所需输入.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-完成输入数据准备工作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-训练代码与参数配置更改.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-训练模型并测试效果.mp4.mp4
│&nBSp;&nBSp;├─7_YOLO-V4版本算法解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-V4版本整体概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-PAN模块解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-激活函数与整体架构总结.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-V4版本贡献解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-数据增强策略分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-DroPBlock与标签平滑方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-损失函数遇到的问题.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-CIOU损失函数定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-NMS细节改进.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-SPP与CSP网络结构.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-SAM注意力机制模块.mp4.mp4
│&nBSp;&nBSp;├─8_V5版本项目配置
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-整体项目概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-训练自己的数据集方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-训练数据参数配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-测试DEMO演示.mp4.mp4
│&nBSp;&nBSp;└─9_V5项目工程源码解读
│&nBSp;&nBSp;└─├┈1-数据源DEBUG流程解读.mp4.mp4
│&nBSp;&nBSp;└─├┈10-完成配置文件解析任务.mp4.mp4
│&nBSp;&nBSp;└─├┈11-前向传播计算.mp4.mp4
│&nBSp;&nBSp;└─├┈12-BottleneckCSP层计算方法.mp4.mp4
│&nBSp;&nBSp;└─├┈13-1 SPP层计算细节分析.mp4.mp4
│&nBSp;&nBSp;└─├┈13-HeAD层流程解读.mp4.mp4
│&nBSp;&nBSp;└─├┈14-上采样与拼接操作.mp4.mp4
│&nBSp;&nBSp;└─├┈15-输出结果分析.mp4.mp4
│&nBSp;&nBSp;└─├┈16-超参数解读.mp4.mp4
│&nBSp;&nBSp;└─├┈17-命令行参数介绍.mp4.mp4
│&nBSp;&nBSp;└─├┈18-训练流程解读.mp4.mp4
│&nBSp;&nBSp;└─├┈19-各种训练策略概述.mp4.mp4
│&nBSp;&nBSp;└─├┈2-图像数据源配置.mp4.mp4
│&nBSp;&nBSp;└─├┈20-模型迭代过程.mp4.mp4
│&nBSp;&nBSp;└─├┈3-加载标签数据.mp4.mp4
│&nBSp;&nBSp;└─├┈4-MosAIc数据增强方法.mp4.mp4
│&nBSp;&nBSp;└─├┈5-数据四合一方法与流程演示.mp4.mp4
│&nBSp;&nBSp;└─├┈6-getItem构建batch.mp4.mp4
│&nBSp;&nBSp;└─├┈7-网络架构图可视化工具安装.mp4.mp4
│&nBSp;&nBSp;└─├┈8-V5网络配置文件解读.mp4.mp4
│&nBSp;&nBSp;└─└┈9-Focus模块流程分析.mp4.mp4
├─7_图像分割实战
│&nBSp;&nBSp;├─10_MaskRcnn网络框架源码详解
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-FPN层特征提取原理解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-RoIPooling层的作用与目的.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-RorAlign操作的效果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈12-整体框架回顾.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-FPN网络架构实现解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-生成框比例设置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-基于不同尺度特征图生成所有框.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-RPN层的作用与实现解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-候选框过滤方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-Proposal层实现方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-DetectionTarget层的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-正负样本选择与标签定义.mp4.mp4
│&nBSp;&nBSp;├─11_基于MASK-RCNN框架训练自己的数据与任务
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Labelme工具安装.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-使用labelme进行数据与标签标注.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-完成训练数据准备工作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-maskrcnn源码修改方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-基于标注数据训练所需任务.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-测试与展示模块.mp4.mp4
│&nBSp;&nBSp;├─1_图像分割及其损失函数概述
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-语义分割与实例分割概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-分割任务中的目标函数定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈3-MIOU评估标准.mp4.mp4
│&nBSp;&nBSp;├─2_卷积神经网络原理与参数解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-卷积神经网络应用领域.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-VGG网络架构.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈11-残差网络Resnet.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈12-感受野的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-卷积的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-卷积特征值计算方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-得到特征图表示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-步长与卷积核大小对结果的影响.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-边缘填充方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-特征图尺寸计算与参数共享.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-池化层的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-1整体网络架构.mp4.mp4
│&nBSp;&nBSp;├─3_Unet系列算法讲解
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Unet网络编码与解码过程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-网络计算流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-Unet升级版本改进.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈4-后续升级版本介绍.mp4.mp4
│&nBSp;&nBSp;├─4_unet医学细胞分割实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-医学细胞数据集介绍与参数配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据增强工具.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-Debug模式演示网络计算流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-特征融合方法演示.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-迭代完成整个模型计算任务.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-模型效果验证.mp4.mp4
│&nBSp;&nBSp;├─5_U2NET显著性检测实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-任务目标与网络整体介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-显著性检测任务与目标概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-编码器模块解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-解码器输出结果.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-损失函数与应用效果.mp4.mp4
│&nBSp;&nBSp;├─6_Deeplab系列算法
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-Deeplab分割算法概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-空洞卷积的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-感受野的意义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-SPP层的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-ASPP特征融合策略.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-DeeplabV3Plus版本网络架构.mp4.mp4
│&nBSp;&nBSp;├─7_基于DeeplabV3+版本进行VOC分割实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-PascalVoc数据集介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-项目参数与数据集读取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-网络前向传播流程.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-ASPP层特征融合.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-分割模型训练.mp4.mp4
│&nBSp;&nBSp;├─8_医学心脏视频数据集分割建模实战
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-数据集与任务概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-项目基本配置参数.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-任务流程解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-文献报告分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-补充：视频数据源特征处理方法概述.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈6-补充：R(2plus1)D处理方法分析.mp4.mp4
│&nBSp;&nBSp;└─9_物体检测框架-MaskRcnn项目介绍与配置
│&nBSp;&nBSp;└─├┈0-Mask-Rcnn开源项目简介.mp4.mp4
│&nBSp;&nBSp;└─├┈0-参数配置.mp4.mp4
│&nBSp;&nBSp;└─└┈0-开源项目数据集.mp4.mp4
├─8_行为识别实战
│&nBSp;&nBSp;├─1_slowfast算法知识点通俗解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-slowfast核心思想解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-核心网络结构模块分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-数据采样曾的作用.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-模型网络结构设计.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈5-特征融合模块与总结分析.mp4.mp4
│&nBSp;&nBSp;├─2_slowfast项目环境配置与配置文件
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-环境基本配置解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-目录各文件分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-配置文件作用解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-测试DEMO演示1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-训练所需标签文件说明.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-训练所需视频数据准备.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-视频数据集切分操作.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈8-完成视频分帧操作.mp4.mp4
│&nBSp;&nBSp;├─3_slowfast源码详细解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-模型所需配置文件参数读取1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈10-RoiAlign与输出层1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据处理概述1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-dataloADer数据遍历方法1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-数据与标签读取实例1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-图像数据所需预处理方法1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-slow与fast分别执行采样操作1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈7-分别计算特征图输出结果1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈8-slow与fast特征图拼接操作1.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈9-resnetBolock操作1.mp4.mp4
│&nBSp;&nBSp;├─4_基于3D卷积的视频分析与动作识别
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-3D卷积原理解读.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-UCF101动作识别数据集简介.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-测试效果与项目配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-视频数据预处理方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-数据Batch制作方法.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-3D卷积网络所涉及模块.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-训练网络模型.mp4.mp4
│&nBSp;&nBSp;├─5_视频异常检测算法与元学习
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-异常检测要解决的问题与数据集介绍.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-基本思想与流程分析.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-预测与常见问题.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-Meta-Learn要解决的问题.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-学习能力与参数定义.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-如何找到合适的初始化参数.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-MAML算法流程解读.mp4.mp4
│&nBSp;&nBSp;├─6_视频异常检测CVPr2021论文及其源码解读
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈1-论文概述与环境配置.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈2-数据集配置与读取.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈3-模型编码与解码结构.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈4-注意力机制模块打造.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈5-损失函数的目的.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;├┈6-特征图生成.mp4.mp4
│&nBSp;&nBSp;│&nBSp;&nBSp;└┈7-MetaLearn与输出.mp4.mp4
│&nBSp;&nBSp;└─7_基础补充-Resnet模型及其应用实例
│&nBSp;&nBSp;└─├┈1-医学疾病数据集介绍.mp4.mp4
│&nBSp;&nBSp;└─├┈2-Resnet网络架构原理分析.mp4.mp4
│&nBSp;&nBSp;└─├┈3-dataloADer加载数据集.mp4.mp4
│&nBSp;&nBSp;└─├┈4-Resnet网络前向传播.mp4.mp4
│&nBSp;&nBSp;└─├┈5-残差网络的shortcut操作.mp4.mp4
│&nBSp;&nBSp;└─├┈6-特征图升维与降采样操作.mp4.mp4
│&nBSp;&nBSp;└─└┈7-网络整体流程与训练演示.mp4.mp4
└─9_2022论文必备-Transformer实战系列
└─├─10_MedicalTransformer源码解读
└─│&nBSp;&nBSp;├┈1-项目环境配置1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-医学数据介绍与分析1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-基本处理操作1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-AxialAttention实现过程1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-位置编码向量解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-注意力计算过程与方法1.mp4.mp4
└─│&nBSp;&nBSp;└┈7-局部特征提取与计算1.mp4.mp4
└─├─11_商汤LoFTR算法解读
└─│&nBSp;&nBSp;├┈1-特征匹配的应用场景.mp4.mp4
└─│&nBSp;&nBSp;├┈10-总结分析.mp4.mp4
└─│&nBSp;&nBSp;├┈2-特征匹配的基本流程分析.mp4.mp4
└─│&nBSp;&nBSp;├┈3-整体流程梳理分析.mp4.mp4
└─│&nBSp;&nBSp;├┈4-CrossAttention的作用与效果.mp4.mp4
└─│&nBSp;&nBSp;├┈5-transformer构建匹配特征.mp4.mp4
└─│&nBSp;&nBSp;├┈6-粗粒度匹配过程与作用.mp4.mp4
└─│&nBSp;&nBSp;├┈7-特征图拆解操作.mp4.mp4
└─│&nBSp;&nBSp;├┈8-细粒度匹配的作用与方法.mp4.mp4
└─│&nBSp;&nBSp;└┈9-基于期望预测最终位置.mp4.mp4
└─├─12_局部特征关键点匹配实战
└─│&nBSp;&nBSp;├┈1-项目与参数配置解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈10-得到精细化输出结果1.mp4.mp4
└─│&nBSp;&nBSp;├┈11-通过期望计算最终输出1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-DEMO效果演示1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-backbone特征提取模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-注意力机制的作用与效果分析1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-特征融合模块实现方法1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-cross关系计算方法实例1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-粗粒度匹配过程1.mp4.mp4
└─│&nBSp;&nBSp;├┈8-完成基础匹配模块1.mp4.mp4
└─│&nBSp;&nBSp;└┈9-精细化调整方法与实例1.mp4.mp4
└─├─13_项目补充-谷歌开源项目BERT源码解读与应用实例
└─│&nBSp;&nBSp;├┈1-BERT开源项目简介1.mp4.mp4
└─│&nBSp;&nBSp;├┈10-构建QKV矩阵1.mp4.mp4
└─│&nBSp;&nBSp;├┈11-完成Transformer模块构建1.mp4.mp4
└─│&nBSp;&nBSp;├┈12-训练BERT模型1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-项目参数配置1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-数据读取模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-数据预处理模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-Embedding层的作用1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-加入额外编码特征1.mp4.mp4
└─│&nBSp;&nBSp;├┈8-加入位置编码特征1.mp4.mp4
└─│&nBSp;&nBSp;├┈9-mask机制1.mp4.mp4
└─│&nBSp;&nBSp;└┈tfrecord制作1.mp4.mp4
└─├─14_项目补充-基于BERT的中文情感分析实战
└─│&nBSp;&nBSp;├┈1-中文分类数据与任务概述1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-读取处理自己的数据集1.mp4.mp4
└─│&nBSp;&nBSp;└┈3-训练BERT中文分类模型1.mp4.mp4
└─├─1_课程介绍
└─│&nBSp;&nBSp;└┈课程介绍1.mp4.mp4
└─├─2_自然语言处理通用框架BERT原理解读
└─│&nBSp;&nBSp;├┈1-BERT任务目标概述.mp4.mp4
└─│&nBSp;&nBSp;├┈10-训练实例.mp4.mp4
└─│&nBSp;&nBSp;├┈2-传统解决方案遇到的问题1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-注意力机制的作用1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-self-attention计算方法1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-特征分配与softmax机制1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-Multi-heAD的作用1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-位置编码与多层堆叠1.mp4.mp4
└─│&nBSp;&nBSp;├┈8-transformer整体架构梳理.mp4.mp4
└─│&nBSp;&nBSp;└┈9-BERT模型训练方法.mp4.mp4
└─├─3_Transformer在视觉中的应用VIT算法
└─│&nBSp;&nBSp;├┈1-transformer发家史介绍1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-对图像数据构建patch序列1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-VIT整体架构解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-CNN遇到的问题与窘境1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-计算公式解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-位置编码与TNT模型1.mp4.mp4
└─│&nBSp;&nBSp;└┈7-TNT模型细节分析1.mp4.mp4
└─├─4_VIT算法模型源码解读
└─│&nBSp;&nBSp;├┈1-项目配置说明1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-输入序列构建方法解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-注意力机制计算1.mp4.mp4
└─│&nBSp;&nBSp;└┈4-输出层计算结果1.mp4.mp4
└─├─5_swintransformer算法原理解析
└─│&nBSp;&nBSp;├┈1-swintransformer整体概述1.mp4.mp4
└─│&nBSp;&nBSp;├┈10-分层计算方法1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-要解决的问题及其优势分析1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-一个block要完成的任务1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-获取各窗口输入特征1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-基于窗口的注意力机制解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-窗口偏移操作的实现1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-偏移细节分析及其计算量概述1.mp4.mp4
└─│&nBSp;&nBSp;├┈8-整体网络架构整合1.mp4.mp4
└─│&nBSp;&nBSp;└┈9-下采样操作实现方法1.mp4.mp4
└─├─6_swintransformer源码解读
└─│&nBSp;&nBSp;├┈1-数据与环境配置解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-图像数据patch编码1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-数据按window进行划分计算1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-基础attention计算模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-窗口位移模块细节分析1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-patchmerge下采样操作1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-各block计算方法解读1.mp4.mp4
└─│&nBSp;&nBSp;└┈8-输出层概述1.mp4.mp4
└─├─7_基于Transformer的detr目标检测算法
└─│&nBSp;&nBSp;├┈1-DETR目标检测基本思想解读1.mp4.mp4
└─│&nBSp;&nBSp;├┈2-整体网络架构分析1.mp4.mp4
└─│&nBSp;&nBSp;├┈3-位置信息初始化query向量1.mp4.mp4
└─│&nBSp;&nBSp;├┈4-注意力机制的作用方法1.mp4.mp4
└─│&nBSp;&nBSp;└┈5-训练过程的策略1.mp4.mp4
└─├─8_detr目标检测源码解读
└─│&nBSp;&nBSp;├┈1-项目环境配置解读2.mp4.mp4
└─│&nBSp;&nBSp;├┈2-数据处理与dataloADer2.mp4.mp4
└─│&nBSp;&nBSp;├┈3-位置编码作用分析2.mp4.mp4
└─│&nBSp;&nBSp;├┈4-backbone特征提取模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈5-mask与编码模块1.mp4.mp4
└─│&nBSp;&nBSp;├┈6-编码层作用方法1.mp4.mp4
└─│&nBSp;&nBSp;├┈7-Decoder层操作与计算1.mp4.mp4
└─│&nBSp;&nBSp;├┈8-输出预测结果1.mp4.mp4
└─│&nBSp;&nBSp;└┈9-损失函数与预测输出1.mp4.mp4
└─└─9_MedicalTrasnformer论文解读
└─└─├┈1-论文整体分析.mp4.mp4
└─└─├┈2-核心思想分析.mp4.mp4
└─└─├┈3-网络结构计算流程概述.mp4.mp4
└─└─├┈4-论文公式计算分析.mp4.mp4
└─└─├┈5-位置编码的作用与效果.mp4.mp4
└─└─└┈6-拓展应用分析.mp4.mp4

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