暑假到研究所前雛形規劃

--- lang: zh-tw --- 暑假到研究所前雛形規劃 === ## 中正新生行事曆 [Link](https://freshman.ccu.edu.tw/files/123456789.pdf) | 時間 | 內容 | 狀態 | |:------:|:-----------:|:----:| | 7/1~7/20 | 學籍系統登錄 | Done | | 8/14~ | 繳交學雜費 | | | 8/24 ~ 8/28 | 去中正上LabView課程 | | | ~8/30 | 填寫【新生兵役資料表】(至新生表單處下載)，請於109年8月30日前寄回或繳交至學務處學生安全組| done | | ~ | ==「學術倫理教育」== 課程: [Link](https://ethics.moe.edu.tw/courses/my/) 每天都要看2篇| ==done [修課證明連結](https://drive.google.com/file/d/1V7G_iQTwa4ajV3Qqe8_ZC2_f7FgxZNPI/view?usp=sharing)== | | ~ | ==中正選課系統[Link](https://kiki.ccu.edu.tw/~ccmisp06/cgi-bin/class_new/)==|| | 8/31~9/4| ==**LabView課程**== | ==地點: 創新大樓201 時間: 早上9:30開始== | | 8/31 | 1.校內學生健康檢查, 地點：本校大禮堂($620), 時間: 9:50 ~ 10:40, 要帶學生健康檢查資料表 | ==Done== | | 8/31 | 領學生證 | ==地點:教學組== | | 9/1 | **指導碩士論文同意書-拿給教授簽(教授會幫我拿去交給系辦)** | ==Done== | | 9/3(禮拜四) | **新生始業典禮** ==Google試算表有詳細流程...等== | ==地點: 本校大禮堂時間: 8:30~10:00==| | ==9/2 ~ 9/5== | ==**新生第一階段選課**== | 教學組分機 11212 、 11208| | ==9/7 ~ 9/21== | ==第二階段選課加退== | 教學組分機 11212 、 11208| | 9/7 | 開始上課 | | | | | | ## 每日行程 (約10hr, 禮拜日休息) | 時間 | 學習內容 | |:------:|:-----------:| | 早上 08:00~12:40|**[ML & AI](https://www.youtube.com/channel/UC2ggjtuuWvxrHHHiaDH1dlQ) , [Pytorch Document](https://pytorch.org/docs/stable/index.html) , [Pytorch Example](https://github.com/pytorch/examples) , ==[醫學訊號分析原理與 MATLAB 程式應用實作](https://www.youtube.com/playlist?list=PLx_IWc-RN82uKOdafF4v4U5R_u4qmYaiu)==**| | 下午 13:10~16:30| [數位影像處理](https://www.youtube.com/playlist?list=PLI6pJZaOCtF2fjFxpVGAqWgENVZw69QD2), [二維自動化光學檢測及應用](https://www.youtube.com/playlist?list=PLI6pJZaOCtF0yLRQrV7JOBUaAfJ8Q-elm), [數位信號處理](https://www.youtube.com/playlist?list=PLI6pJZaOCtF2UPD5TUmLDbBAj-kU5x90Y), [作業系統](https://www.youtube.com/playlist?list=PLS0SUwlYe8czigQPzgJTH2rJtwm0LXvDX), [生物統計學](https://www.youtube.com/playlist?list=PLuz2BOX_eyHGm8F0Dx7k60lUwvgVf7Mnd)| | 晚上 19:30~21:30 (讀1休1)| [Leetcode](https://leetcode.com/) , [解題思路](https://www.youtube.com/user/xxfflower) 看論文 ![](https://i.imgur.com/WV5atY0.jpg) ![](https://i.imgur.com/eKvpmQq.jpg)| ## 學習進度 | 日期 | 早上 | 下午 | 晚上 | |:----:|:-----------:|:-----:|:-----:| | 6/25 | Pytorch-Handbook: Ch01-1_tensor_tutorial | 生物統計學01~04 | Leetcode + Python decoractor | | 6/27 | [Pytorch-Deep Learning (02~04)](https://www.youtube.com/watch?v=9j-_dOze4IM&list=PLQVvvaa0QuDdeMyHEYc0gxFpYwHY2Qfdh&index=4) , Pytorch-Handbook: Ch03-3_neural_networks_tutorial , **下次要開始讀 torch.nn & torch.nn.functional & torch.optim**| 作業系統-Page Replacement + Leetcode | **Take a rest** | | 7/1 | DEEP LEARNING WITH PYTORCH: A 60 MINUTE BLITZ + **ML Lecture (2,3-1)**| 數位影像處理單元二 + 單元三 | Leetcode + Python Iterable | | 7/2 | **ML Lecture (4,5)** + **醫學訊號分析(s1, s2, s3-2)**| 作業系統(15A ~ 16D) | **Take a rest** | | 7/3 | **醫學訊號分析(3-3, 4-1, 4-2)** + Pytorch-book(Ch03-1)| Pyotch-book(Ch03-2) + 數位影像處理單元四 | Leetcode | | 7/4 | **醫學訊號分析(5-1~5-3, 6-1)**+ Pytorch-book(Ch03-1) | Pyotch-book(Ch03-2) + | **Take a rest** | | 7/5 | **Take a rest** | **Take a rest** | **Take a rest** | | 7/6 | **醫學訊號分析(6-2)** + Pytorch-book(Ch04) + **Implement ResNet**| 作業系統(17-A ~ 18-A) + **ML Lecture (7, 8)** | 複習Pytorch-book(Ch04) + ML Lecture (9) + Leetcode | | 7/7 | **醫學訊號分析(7-1~7-3)** + Pytorch-book(Ch05) | 數位影像處理單元五 + Leetcode | **Take a rest** | | 7/8 | **Review{醫學訊號分析(7-1~7-3) + Pytorch-book(Ch02~Ch04)}** | **Review{Pytorch-book(Ch05)}** + ML Lecture (9~12) | Leetcode + 生物統計學(05) | | 7/9 | 生物統計學(06, 07) | DL-CV(D1~D5) + **醫學訊號分析(8-1~8-3)**| **Take a rest** | | 7/10 | 數位影像處理單元六+DL-CV(Day6) | 數位影像處理單元七八 + **ML Lecture (13)** | **Take a rest** | | 7/11 | 搬宿舍 | 搬宿舍 | **Take a rest** | | 7/12 | **Take a rest** | **Take a rest** | **Take a rest** | | 7/13 | **DL-CV(Day7~Day11) + 讀RegNet論文(1. ~ 2) + Train RegNet on Cifar-10** | **讀RegNet論文(3 ~ 3.2)** + DLHLP-Controllable Chatbot| LeetCode | | 7/14 | **讀RegNet論文(Done)** | 二維自動化光學檢測及應用(u01 ~ u02) | **Take a rest** | | 7/15 | **期刊論文閱讀技巧** + ML Lecture(14~15)| ML Lecture (16~18) + DL-CV(~Day17) | LeetCode | | 7/16 | 領畢業證書 | 交畢業證書 | **Take a rest** | | 7/17 | 複習DL-CV(Day01~Day19) | ML Lecture(18~21) | **Leetcode** | | 7/18 | 複習Pytorch book| ML Lecture(22~23) | **LeetCode** | | 7/20 | DL-CV(Day25) + **(R-CNN, Fast R-CNN, Faster R-CNN)** | DL-CV(Day26, 27) + Faster R-CNN | **Take care of dad all day** | | 7/21 | **二維自動化光學檢測及應用(==Done==)**| DL-CV(Day28) + ML Lecture(Ensemble) + 數位信號處理(第一、二單元) | **Take a rest** | | 7/22 | 數位信號處理(第三單元) + ML Lecture(Reinforcement Learning) + Advanced DL(Review) | **Take a rest** | **Take a rest** | | 7/23 | 去中正聽碩士口試 | 去中正聽碩士口試 | **Take a rest ** | | 7/24 | **Take a rest** | **Take a rest** | **Take a rest** | | 7/25 | **Implement GAN** + DL-CV + Review Pytorch book | Advanced ML(~video5) + GAN2018(Lecture1) | **Take a rest** | | 7/27 | Pygame(Hangman game) | DL-CV + New Optimizer(DL) | Expert Python | | 7/28 | Advanced ML(~video8) + DeepLearning Book(Ch02) | Pytorch review | **Take a rest** | | 7/29 | DeepLearning Book(Ch03) + Review Pytorch(dataset, DataLoader) | DL-CV + Advanced ML(~video13) + MATLAB教學(~video2) | Leetcode | | 7/30 | **複習Python for Data Analysis(ch04 Numpy Basis)** + DeepLearning Book(Ch04) | MATLAB教學(~video4) + MATLAB程式設計與影像處理(~video2) | images_tb(Ch01) | | 7/31 | Data Analysis with Python - Full Course + **複習Python for Data Analysis** | **PyTorch for Deep Learning - Full Course(~4:45:13)** | LeetCode | | 8/1 | **PyTorch for Deep Learning - Full Course(Done)** | MATLAB程式設計與影像處理(~video6) | **Take a rest** | | 8/2 | **Take a rest** | **Data_Science(Ch02, Ch03) + Python for Data Analysis(Ch05 pandas)** | **Take a rest** | | 8/3 | Data_Science(~Ch05) + DeepLearning(~Ch5-2) | MATLAB程式設計與影像處理(~Lesson8) + MATLAB教學(~video5) | | | 8/4 | DeepLearning(~5-4) + Data_Science(~Ch06) + MATLAB教學 - 06 + | MATLAB程式設計與影像處理(~Lesson9)| | | 8/5 | Review 醫學訊號分析原理與 MATLAB 程式應用實作 | 學術倫理教育課程(~0104) | 學術倫理教育課程(~0106)| | 8/6 | DeepLearning(~5-6) + Python for Data Analysis (Ch07) | AdvancedML(~video14) + MATLAB教學(影像處理一，二) + 學術倫理教育課程(~0106) | 學術倫理教育課程(~0110)| | 8/7 | MATLAB教學(~video12) | | | | 8/8 | Python for Data Analysis (Ch08) + 10分鐘學簡報(video64~video62) + Python_Plays_GTA(~video4) | OpenCV Python for Beginners(~2:04:34) + AdvancedML(~video18) | | | 8/10 | 數位影像處理(單元二~三) + 數位信號處理器(單元一) | 數位信號處理器(單元二~三) + NextStepML(Anomaly Detection) | OpenCV Python for Beginners(~3:32:08) | | 8/11 | Python for Data Analysis (Ch09) + 數位影像處理(單元四-half) | 數位影像處理(單元四) + Attack ML Models + 10分鐘學簡報(video61~video60) | OpenCV Python for Beginners(~4:32:18) | | 8/12 | Python for Data Analysis(Ch10) | 數位影像處理(單元五) + OpenCV Python for Beginners(~6:36:18) | | | 8/14 | OpenCV Python for Beginners | OpenCV Python for Beginners(Done) + 數位影像處理(單元七) | | | 8/16 ~ 8/18 | CVGIP | CVGIP | CVGIP | | 8/19 | DL-CV review(Day1~10) + OpenCV Python for Beginners review(30%) | OpenCV Python for Beginners review(done) + Explainable ML | take a rest | | 8/20 | Life-Long Learning + Meta Learning + More about Auto-encoder | Flow-based Generative Model + Transformer | ELMO + BERT + GPT| | 8/21 | Python for Data Analysics (Ch10~12) | Go to Hospital | Pytorch | | 8/22 | Pytorch | Pytorch | Pytorch | | 8/23 | Pytorch | Pytorch | Pytorch + Network Compression | | 8/24 | GAN2018(Lecture1~3) | GAN2018(Lecture4, 5) | **Take a rest** | | 8/25 | **Take a rest** | **Take a rest** | **Take a rest** | | 8/26 | Preview LabView | | | | 8/30 | 搬宿舍 | 搬宿舍 | 二維自動化光學檢測及應用(u01~u02) | | 8/31 | LabView課程背多益單字(Unit1) | LabView課程 | **MatLab教學(02~03)** **複習OpenCV** **Review今日課程(Labview)** Review多益(Unit1) | | 9/1 | MATLAB教學(04) LabView課程背多益單字(Unit2) | LabView課程 | 黃能富教授計算機網路概論(1A~1B) 背多益單字(Unit2) 複習OpenCV | | 9/2 | MATLAB教學(05) LabView課程背多益單字(Unit3)| LabView課程整理實驗室 | 黃能富教授計算機網路概論(1C) 複習OpenCV(Done) LabViewCore1(p1~p290) | | 9/3| | MATLAB教學(06, 08) | | MATLAB教學(09) 黃能富教授計算機網路概論(2A~2E) | | 9/4 | MATLAB教學-影像處理二 | | | | 9/7 | | | 演算法Ch2-Algorithm analysis 遙測原理簡介多益單字(~Unit8) | | 9/8 | 多益單字(Unit9) 黃能富教授計算機網路概論(1A~1B) | | 黃能富教授計算機網路概論(1C) + 遙測原理簡介 | | 9/9 | 黃耀廷演算法(一), Peak Finding, 多益單字(Unit10) | | 黃耀廷演算法(DP, Shortest Path, P, NP) | | 9/10 | DL-CV(Review) | | | | 9/11 | Algorithm | ==Faster RCNN(Paper) done== | | | 9/12 | 中正計算機網路(Ch1) | 演算法(Divide and Conquer, DP) | Take a rest | | 9/14 | Mask rcnn| | Deep Learning Theory | | 9/15 | Review Pytorch | ResNet paper | 黃能富(Application Layer) | | 9/16 | 多益單字(Unit17) | 遙測HW | 做報告, Deep Learning Theory(done) | | 9/17 | 多益單字(Unit18, 19), Advanced Topic DL(~2) | | Advanced Topic DL(3) Review電腦網路 Preview演算法(DP) | | 9/18 | 多益單字(Unit20, 21) Advanced Topic DL(3) | | | | 9/19 | Review Computer_Network, Algorith | Advanced Topic DL(~11) | | | 9/21 | | | 多益單字(Unit22, 23) Advanced Topic DL(~14) | | 9/22 | 演算法(Shortest-Path Problems & P, NP, NP-completeness) | | 多益單字(Unit24) 生醫HW1 演算法(P, NP, NP-completeness) | | 9/23 | 多益單字(Unit24) 演算法(P, NP, NP-completeness) | | Advanced Topic DL(~18) 多益單字(Unit25) | | 9/24 | 多益單字(~Unit27) 演算法 | | | | 9/26 | 電腦網路 | 演算法 LabView | | | 9/28 | | HW | LabView| | 9/29 | 多益單字(~Unit32) LabView | 遙測作業(Done) 解剖學(一)運動 | | | 9/30 | 多益單字(~Unit35) 解剖學(二)循環 | | | | 10/5 | | 遙測+生醫作業 | 解剖學(一)運動多益單字(Unit36) 演算法(Shortest Path) | | 10/6 | 多益單字(~Unit38) 解剖學(二~三) | 複習生醫影像 Data_Augmentation | 黃能富教授計算機網路概論(2A~2C)_ApplicationLayer | | 10/7 | 多益單字(~Unit40) 複習生醫影像(10/7) 複習遙測影像 | Review Computer_Network(Book) | 演算法(2020_0911, 2020_0918) 多益單字(~Unit41) | | 10/8 | 多益單字(~Unit42) 演算法(P, NP, NP-completeness) | | | | 10/9 | 電腦網路(Note) | 演算法(Shortest_path, SAT) | | | 10/11 | | 電腦網路(Book) | | | 10/12 | | Scirtothrips(train_on_yolov3) | Machine_Learning(Gradient_Descent, Classification) 多益單字(~Unit43) | | 10/13 | 多益單字(~Unit45), Deep Learning with PyTorch: A 60 Minute Blitz, Machine_Learning(Logistic Regression) | 計算機專題(10/12心得) | OpenCV(Ch02~Ch03) Machine_Learning(Deep_Learning, Backpropagation) | | 10/14 | 多益單字(~Unit47) Machine_Learning(Tips_for_DNN) | Remote_Sensing(Note) | 演算法 Machine_Learning(CNN) | | 10/15 | 多益單字(~Unit48) OpenCV(~Ch06) | | | | 10/16 | | | | | 10/17 | 演算法 | 眼算法 | | | 10/19 | | Paper | 演算法(10/16) Machine_Learning(~L14) | | 10/20 | 多益單字(~50) 演算法(Divide and Conquer, Dynamic Programming) | Paper | 演算法(Shortest Path, P NP, SAT) | | 10/21 | 演算法 | 演算法 | 演算法 | | 10/22 | 演算法 | 演算法 | 演算法 | | 10/23 | | 演算法作業 | 演算法作業, 複習計算機網路 | | 10/24 | 計算機網路 | | | | 10/26 | | Paper | Paper + 生醫複習 | | 10/27 | Paper, 遙測複習 | Paper | 計算方法(DP, Shortest Path) + 2019作業 | | | | | | | | | | | ## 讀書資源 --- ### 碩一上 1. 遙測科學概論: [Link](https://sites.google.com/view/ncuxocw/%E9%96%8B%E6%94%BE%E8%AA%B2%E7%A8%8B/%E8%AA%8D%E8%AD%98%E5%9C%B0%E7%90%83%E7%B3%BB%E5%88%97/%E9%81%99%E6%B8%AC%E7%A7%91%E5%AD%B8%E5%B0%8E%E8%AB%96) 2. 影像處理: [Link](https://sites.google.com/site/ncuocw/course/63016/document) 3. 中正計算方法: [Link](https://www.youtube.com/playlist?list=PLry9mqkbzijKYtoqYtQ9n0TOgfW0_1vUc) 4. ### Machine Learning & Deep learning --- **DEEP LEARNING WITH PYTORCH: A 60 MINUTE BLITZ: [LINK](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html#deep-learning-with-pytorch-a-60-minute-blitz)** --- #### Document + Pytorch: https://pytorch.org/docs/stable/index.html + Tensorflow: https://www.tensorflow.org/api_docs/python/ --- #### Youtube Playlist + Machine Learning: https://www.youtube.com/watch?v=CXgbekl66jc&list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49 + Advanced Topic in ML: https://www.youtube.com/watch?v=IzHoNwlCGnE&list=PLJV_el3uVTsPMxPbjeX7PicgWbY7F8wW9 + Structured Learning: https://www.youtube.com/watch?v=5OYu0vxXEv8&list=PLJV_el3uVTsNHQKxv49vpq7NSn-zim18V + Deep Learning Theory: https://www.youtube.com/watch?v=KKT2VkTdFyc&list=PLJV_el3uVTsOh1F5eo9txATa4iww0Kp8K + GAN_2017: https://www.youtube.com/watch?v=G0dZc-8yIjE&list=PLJV_el3uVTsMd2G9ZjcpJn1YfnM9wVOBf + GAN_2018: https://www.youtube.com/watch?v=DQNNMiAP5lw&list=PLJV_el3uVTsMq6JEFPW35BCiOQTsoqwNw + Deep Reforcement Learning: https://www.youtube.com/watch?v=z95ZYgPgXOY&list=PLJV_el3uVTsODxQFgzMzPLa16h6B8kWM_ + Next step of ML_2019: https://www.youtube.com/watch?v=XnyM3-xtxHs&list=PLJV_el3uVTsOK_ZK5L0Iv_EQoL1JefRL4 + Deep Learning for NLP_2020: https://www.youtube.com/watch?v=nER51ZyJaCQ&list=PLJV_el3uVTsO07RpBYFsXg-bN5Lu0nhdG + ==Machine Learning Foundation(Warning of Math)==: https://www.youtube.com/watch?v=nQvpFSMPhr0&list=PLXVfgk9fNX2I7tB6oIINGBmW50rrmFTqf + ==Machine Learning Technique(Warning of Math)==: https://www.youtube.com/watch?v=A-GxGCCAIrg&list=PLXVfgk9fNX2IQOYPmqjqWsNUFl2kpk1U2 --- #### Github + Hands on Machine Learning: https://github.com/ageron/handson-ml2 + Pytorch Hand Book: https://github.com/zergtant/pytorch-handbook + Pytorch Official Example: https://github.com/pytorch/examples + Pytorch Tutorial: https://github.com/yunjey/pytorch-tutorial + Pytorch book: https://github.com/chenyuntc/pytorch-book --- #### Colab + PyTorch_Introduction.ipynb: https://colab.research.google.com/drive/1Xed5YSpLsLfkn66OhhyNzr05VE89enng#scrollTo=-m-ml0NoMTim + PyTorch_Practice: https://colab.research.google.com/drive/1pzjsuDYiA5SXG7sEf3pZZ6Vr_IlhohbQ#scrollTo=6l1pQR1WGy7T + Pytorch-book-ch04: https://colab.research.google.com/drive/18d0MPnCKd2uTOHg9cbev4iXQkki40U-D#scrollTo=Aj8udBWO7Hqw + Pytorch-book-ch05: https://colab.research.google.com/drive/1lmobD5Q6cDV6uunbgXMgiaQL1NdXJu5W#scrollTo=5P2FxuDTlht4 + Cifar-10 (ResNet & RegNet): https://colab.research.google.com/drive/16Sxj1hcEoKdkPH6rgfd4xG6prXN1mmQZ + Anime **GAN**: https://colab.research.google.com/drive/1q6LgTgGCTIkqqSaL3SdeWVTX7B2owvDY#scrollTo=dfxLlq7e4E7f --- #### Pytorch Note or Tips: - PyTorch Recipes: [Link](https://pytorch.org/tutorials/recipes/recipes_index.html) - PyTorch 中模型的使用: [LINK](https://zhuanlan.zhihu.com/p/73893187) - Pytorch Facial Keypoints Prediction: [LINK](https://medium.com/diving-in-deep/facial-keypoints-detection-with-pytorch-86bac79141e4) - Pytorch Initialize: [Link](https://blog.csdn.net/ganxiwu9686/article/details/103297952) --- #### **Image Detection Related** - Faster R-CNN: [Link](https://zhuanlan.zhihu.com/p/31426458)(==詳解==) [Link](https://arxiv.org/pdf/1506.01497.pdf)(==Paper==) --- #### **PyTorch for Deep Learning - Full Course** 1. **Linear-regression**:https://colab.research.google.com/drive/1k6-mWckth55eqHuMpfLMOMWrk6TIw8KO#scrollTo=IOJEF_nFkDD3 2. **Logistic-regression**:https://colab.research.google.com/drive/1SqWiDi5_7NYjB6miRciQcLX0K44mXXNb 3. **Cifar10-CNN**:https://colab.research.google.com/drive/1SBmue2fxGXMOz2vb_Ia_t_-aRuK-pkDx#scrollTo=WiCSKTZaObB2 --- #### **Object Detection**: 1. R-CNN(知乎): https://zhuanlan.zhihu.com/p/23006190?refer=xiaoleimlnote 2. Object Detection Algorithms(Medium): https://towardsdatascience.com/r-cnn-fast-r-cnn-faster-r-cnn-yolo-object-detection-algorithms-36d53571365e 3. Pytorch initialize:https://pytorch.org/docs/stable/nn.init.html --- #### Paper: ==AI 所有領域最優資料搜尋神器== — [Papers with Code](https://paperswithcode.com/) 1. **RegNet** - **Designing Network Design Spaces(RegNet)**: https://arxiv.org/pdf/2003.13678.pdf - **Regnet Implement(fork)**: https://github.com/wilile26811249/regnet - **RegNet translate and interpretation** https://blog.csdn.net/qq_41185868/article/details/105278487#2.%20Related%20Work --- ### Matlab 1. **MATLAB教學**:https://www.youtube.com/playlist?list=PLVHBjRDK0kALcQMwAFbR5q2driYZCHNIx 2. **MATLAB程式設計與影像處理**:https://www.youtube.com/playlist?list=PLx_IWc-RN82vgwbjcVq_KfpBth4UWKu1V #### 影像分割 1. **3D U-NET**:https://zhuanlan.zhihu.com/p/57530767 --- ### Other Resource: 1. 十分鐘學簡報: [Link](https://www.youtube.com/playlist?list=PLdkvZCcLvKbYs5IFuPpMbGed4x31vhmAP) 2. Python Plays: Grand Theft Auto V: [Link](https://www.youtube.com/playlist?list=PLQVvvaa0QuDeETZEOy4VdocT7TOjfSA8a) 3. OpenCV Python for Beginners: [Link](https://www.youtube.com/watch?v=N81PCpADwKQ) 4. Canny Edge Detection: [Link](https://www.youtube.com/watch?time_continue=666&v=PtSgA19sC5g&feature=emb_title) 5. Gaussian and Laplacian Pyramid: [Link](https://www.cnblogs.com/sddai/p/10330756.html) 6. Opencv threshold: [Link](https://blog.csdn.net/on2way/article/details/46812121) 7. BERT by PyTorch: [Link](https://leemeng.tw/attack_on_bert_transfer_learning_in_nlp.html) 8. OpenCV教程: [Link](https://me.csdn.net/sunny2038) 9. IoU、GIoU、DIoU、CIoU: [Link](https://zhuanlan.zhihu.com/p/94799295)