딥러닝 탐구생활

https://arxiv.org/abs/1905.11946 EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksConvolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically study model scaling and identify that carefully balancing narxiv.org오늘은 그 유명한 EfficientNet을 한번 리..

논문 출처: https://arxiv.org/abs/2405.14458 YOLOv10: Real-Time End-to-End Object DetectionOver the past years, YOLOs have emerged as the predominant paradigm in the field of real-time object detection owing to their effective balance between computational cost and detection performance. Researchers have explored the architectural designs, optimarxiv.org Abstract최근 몇 년 동안 YOLO는 real-time object detec..

논문 출처 : https://arxiv.org/abs/2207.02696 YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorsYOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all known real-time object detectors with 30 FPS or higher on GPU V100. YOLOv7-E6 object detector (56 FPSarxiv.org Ab..