Archives for RetinaNet
PP-YOLO is a deep learning framework to detect objects. This framework is based on YOLO4 architecture. This method was published in the form of a Research paper titled as PP-YOLO: An Effective and Efficient Implementation of Object Detector by the researchers of Baidu : Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan…
The post Guide To PP-YOLO: An Effective And Efficient Implementation Of Object Detector appeared first on Analytics India Magazine.
PP-YOLO is a deep learning framework to detect objects. This framework is based on YOLO4 architecture. This method was published in the form of a Research paper titled as PP-YOLO: An Effective and Efficient Implementation of Object Detector by the researchers of Baidu : Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan…
The post Guide To PP-YOLO: An Effective And Efficient Implementation Of Object Detector appeared first on Analytics India Magazine.
In the conventional object detectors, say, R-CNN, initially a set of object locations are generated and then these locations are classified whether they belong to the foreground or background classes using a CNN. This is working of a two-stage detector. In the case of one stage detectors like SSD, the accuracy is more when applied…
The post How RetinaNet Fixes The Shortcomings Of SSD With Focal Loss appeared first on Analytics India Magazine.