Object Detection Series - Deep Learning

Learn object detection in deep learning through a comprehensive video series that builds understanding from fundamental concepts to implementing state-of-the-art architectures from scratch in PyTorch. Start with no prior knowledge of object detection and progressively develop expertise by exploring historical approaches and modern solutions to this computer vision problem. Master essential evaluation metrics including Intersection over Union (IoU), Non Max Suppression, and Mean Average Precision (mAP) through detailed explanations and hands-on PyTorch implementations. Apply theoretical knowledge by implementing complete object detection architectures including YOLOv1 and YOLOv3 from the ground up, gaining deep insights into how these influential models work internally. Build a solid foundation for understanding and implementing state-of-the-art object detection papers through practical coding experience and conceptual understanding of the field's evolution and key techniques.