Resources

News

1. https://towardsdatascience.com/how-to-train-yolox-on-a-custom-dataset-bb2f94cdb038. Paper: https://arxiv.org/abs/2107.08430

Tutorials

1. https://debuggercafe.com/ 

2. What is YOLO algorithm? | Deep Learning Tutorial 31: https://www.youtube.com/watch?v=ag3DLKsl2vk&t=601s

3. https://thigiacmaytinh.com/ 

4. https://courses.cs.washington.edu/courses/cse576/20sp/ 

5. https://www.cs.cornell.edu/courses/cs5670/2021sp/lectures/lectures.html 

6. https://www.miai.vn/ 

Tools

1. https://www.pytorchlightning.ai/index.html 

2. Tool Learning with Foundation Models: https://arxiv.org/pdf/2304.08354.pdf , https://github.com/OpenBMB/BMTools 

Self-supervised Learning

1. Lightly SSL: https://github.com/lightly-ai/lightly 

2. https://github.com/vturrisi/solo-learn 

3. https://github.com/ImaGonEs/all4one 

4. https://github.com/Westlake-AI/openmixup 

5. https://github.com/open-mmlab/mmselfsup 

Web services

1. Django REST framework: https://www.django-rest-framework.org/ 

Visualize & Debug Machine Learning Models

1. https://wandb.ai/wandb/getting-started/reports/Visualize-Debug-Machine-Learning-Models--VmlldzoyNzY5MDk 

2. https://wandb.ai/site 

Machine learning platform

1. https://www.kaggle.com/ 

2. https://colab.research.google.com/?hl=vi 

3. https://www.tensorflow.org/ 

4. https://orangedatamining.com/ 

5. https://neptune.ai/ 

Books

1. Computer Vision: Algorithms and Applications, 2nd ed. © 2022 Richard Szeliski, The University of Washington, https://szeliski.org/Book/

2. http://szeliski.org/RichardSzeliski.htm 

Machine learning

1. Stanford CS229: Machine Learning - Andrew Ng, 2018, https://www.youtube.com/watch?v=jGwO_UgTS7I&t=554s

Multimodal Image-text Classification

1. https://vaclavkosar.com/ml/Multimodal-Image-Text-Classification 

YOLO

1. https://learnopencv.com/performance-comparison-of-yolo-models/ 

2. https://medium.com/geekculture/large-scale-object-detection-tracking-with-yolov5-package-c8eca66b80b6 

3. https://medium.com/augmented-startups/is-pp-yoloe-better-than-yolov5-yolox-988386969bcf 

4. How to Deploy YOLOv7 to Jetson Nano (roboflow.com) 

5. https://blog.paperspace.com/benchmarking-yolov6-yolov7-paperspace-roboflow-datasets/ 

6. Ultralytics YOLOv8, https://github.com/ultralytics/ultralytics 

MediaPipe

1. https://google.github.io/mediapipe/

2. https://viblo.asia/p/mediapipe-live-ml-solutions-va-ung-dung-ve-bang-hands-gestures-gAm5ymOV5db 

Transformer

1. https://vinbigdata.com/camera-ai/tong-quan-ve-vision-transformer-vit.html 

CNN

1. https://viblo.asia/p/efficientnet-cach-tiep-can-moi-ve-model-scaling-cho-convolutional-neural-networks-Qbq5QQzm5D8 

2. Stanford CS231n: Convolutional Neural Networks for Visual Recognition, Spring 2021, http://cs231n.stanford.edu/; https://cs231n.github.io/convolutional-networks/

3. https://stanford.edu/~shervine/l/vi/teaching/cs-230/cheatsheet-convolutional-neural-networks

4. Hvass Laboratories, Magnus Erik Hvass Pedersen, https://www.hvass-labs.org/, https://github.com/Hvass-Labs/TensorFlow-Tutorials

5. https://www.kaggle.com/phamdinhkhanh/convolutional-neural-network-p1#3.-T%C3%A0i-li%E1%BB%87u

6. https://dlapplications.github.io/2018-07-06-CNN/

7. Đắm mình vào học sâu: https://d2l.aivivn.com/index.html

8. Videos: https://www.youtube.com/watch?v=56ri8v5fM_w

9. Laurence Moroney: Lead AI Advocacy at Google, https://laurencemoroney.com/about.html, https://www.youtube.com/watch?v=KNAWp2S3w94, colab: https://colab.research.google.com/github/lmoroney/mlday-tokyo/blob/master/Lab3-What-Are-Convolutions.ipynb#scrollTo=kDHjf-ehaBqm

Train models

1. https://blog.roboflow.com/how-to-avoid-bias-in-computer-vision-models/ 

Python

1. https://cs231n.github.io/python-numpy-tutorial/

Object detection

1. https://aicurious.io/posts/tim-hieu-yolo-cho-phat-hien-vat-tu-v1-den-v5/

2. https://phamdinhkhanh.github.io/2019/09/29/OverviewObjectDetection.html

3. Huấn luyện YOLO darknet trên google colab: https://phamdinhkhanh.github.io/2020/03/10/DarknetGoogleColab.html

Small Object detection

1. https://binginagesh.medium.com/small-object-detection-an-image-tiling-based-approach-bce572d890ca

2. https://pyimagesearch.com/2022/02/14/image-super-resolution/  

3. Efficient Small-Object Detection in Airport Surface Based on Maintain Feature High Resolution  

Computer Vision Models on Aerial Imagery

1. https://blog.roboflow.com/how-to-use-roboflow-with-aerial-imagery/ 

Face recognition

1. https://phamdinhkhanh.github.io/2020/03/12/faceNetAlgorithm.html

2. https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/

3. https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/ 

4. https://insightface.ai/projects 

5. https://www.miai.vn/2019/09/11/face-recog-2-0-nhan-dien-khuon-mat-trong-video-bang-mtcnn-va-facenet/

6. https://viblo.asia/p/nhan-dien-khuon-mat-voi-mang-mtcnn-va-facenet-phan-1-Qbq5QDN4lD8 

HAR

1. Using YOLO to detect an action from an image or video: https://github.com/ARjunSNair/action-recognition

2. https://github.com/jinwchoi/awesome-action-recognition/blob/master/README.md

3. https://github.com/s-ankur/human-activity-dih18 

4. https://github.com/GajuuzZ/Human-Falling-Detect-Tracks 

Pose estimation

1. https://itzone.com.vn/vi/article/tim-hieu-ve-blazepose-on-device-real-time-body-pose-tracking/ 

Visualization

1. https://www.miai.vn/2021/01/06/nhin-doi-theo-cach-cua-mang-cnn-visualize-feature-maps-heatmap/ 

Image preprocessing

1. https://cloudinary.com/blog/preprocess-images-for-deep-learning-in-python 

2. https://www.analyticsvidhya.com/blog/2022/04/image-augmentation-using-3-python-libraries/#:~:text=Imgaug,%2C%20heatmaps%2C%20and%20segmentation%20maps. 

3. https://github.com/albumentations-team/albumentations 

4. https://github.com/aleju/imgaug 

5. https://neptune.ai/blog/data-augmentation-in-python 

Evaluation

1. https://machinelearningcoban.com/2017/08/31/evaluation/

2. COCO Evaluation: https://cocodataset.org/#detection-eval

Annotation

1. FIFTYONE: https://voxel51.com/docs/fiftyone/ 

Install GPU

1. https://linuxhint.com/install-cuda-on-ubuntu-22-04-lts/ 

2. https://medium.com/analytics-vidhya/install-cuda-11-2-cudnn-8-1-0-and-python-3-9-on-rtx3090-for-deep-learning-fcf96c95f7a1 

3. https://varhowto.com/install-pytorch-ubuntu-20-04/ 

GPU Devices

1. https://hshop.vn/collections/jetson-nano