You Only Look Once: Unified, Real-Time Object Detection | 5 Minute Paper Podcast скачать в хорошем качестве

You Only Look Once: Unified, Real-Time Object Detection | 5 Minute Paper Podcast

📄 You Only Look Once: Unified, Real-Time Object Detection 👥 Authors: Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi 📅 Published: 2015 | arXiv:cs.CV 🏷️ Topics: detection, object, images, yolo, bounding ABSTRACT: We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to spatially separated bounding boxes and associated class probabilities. A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation. Since the whole detection pipeline is a single network, it can be optimized end-to-end directly on detection performance.... TIMESTAMPS: 00:00 - Introduction 01:11 - You hit the nail on... 02:20 - Oh, wait, so if I... 03:28 - Thats right! This figure beautifully... 04:43 - Wow, thats a lot of... 05:48 - Exactly! That real-time capability is... 07:05 - So, its like YOLO is... 08:16 - Thats a huge benefit. Imagine... 09:37 - So, this paper, You Only... DISCLAIMER: This video contains AI-generated synthetic voices inspired by public figures. These voices are artificially created and do not represent the real persons. This content is for educational and research purposes only and is not affiliated with, endorsed by, or sponsored by Chuck Nice, Neil deGrasse Tyson, or any associated organizations. #AIResearch #MachineLearning #DeepLearning #ResearchPaper #PaperSummary #ComputerVision