# CROD: Dirty References Let's use this document to add some references. ### Training a YOLOv3 Object Detection Model with a Custom Dataset * URL: https://towardsdatascience.com/training-a-yolov3-object-detection-model-with-a-custom-dataset-4981fa480af0 * TYPE: Tutorial * LEVEL: Good ### TensorFlow 2 YOLO v3 MNIST detection training tutorial * URL: https://medium.com/analytics-vidhya/tensorflow-v2-1-yolo-v3-mnist-detection-training-tutorial-ea42f5b6be28 * TYPE: Tutorial * LEVEL: Good ### Tensornets * URL: https://github.com/taehoonlee/tensornets * TYPE: Github Repository * LEVEL: Regular ### YOLO Object Detection: Understanding the You Only Look Once Paper * URL:https://hackerstreak.com/yolo-made-simple-interpreting-the-you-only-look-once-paper/ * TYPE: Explanatory article * LEVEL: Good ### Detect Vehicles and People with YOLOv3 and Tensorflow * URL: https://hackerstreak.com/track-vehicles-and-people-using-yolov3-and-tensorflow/ * TYPE: Tutorial * LEVEL: Regular Complementary code: https://github.com/Baakchsu/Vehicle-and-people-tracking-with-YOLOv3- ### Evolution of Object Detection and Localization Algorithms * URL: https://towardsdatascience.com/evolution-of-object-detection-and-localization-algorithms-e241021d8bad * TYPE: Explanatory article * LEVEL: Good ### You Only Look Once: Unified, Real-Time Object Detection * URL: https://arxiv.org/abs/1506.02640 * TYPE: Research paper * LEVEL: Hard Core ### A Gentle Introduction to Object Recognition With Deep Learning * URL: https://machinelearningmastery.com/object-recognition-with-deep-learning/ * TYPE: Article * LEVEL: Informative ### Object Detection with Deep Learning: The Definitive Guide * URL: https://tryolabs.com/blog/2017/08/30/object-detection-an-overview-in-the-age-of-deep-learning/ * TYPE: Article * LEVEL: Informative ### YOLO9000 Better, Faster, Stronger * URL: https://arxiv.org/pdf/1612.08242.pdf * TYPE: Research Paper * LEVEL: Hard Core ### Detectron * URL: https://github.com/facebookresearch/Detectron * TYPE: Github repository * LEVEL: Good