Archives for SSD
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.
Micron Technology has announced the world’s first open-source, heterogeneous-memory storage engine, which has been designed explicitly for solid-state drives and storage-class memory. According to the company website — the legacy storage engines was born in the era of hard disk drives, which has failed to architecturally provide for the increased performance and reduced latency of…
The post Micron Launches Open-Source Storage Engine Designed For SSDs & Storage Class Memory appeared first on Analytics India Magazine.
Machine learning algorithms for image processing have evolved at a tremendous pace. They can now help in the reconstruction of objects in ambiguous images, colouring old videos, detecting the depth in moving videos and much more. One recurring theme in all these machine vision methods is teaching the model to identify patterns in images. The…
The post How The Deep Learning Approach For Object Detection Evolved Over The Years 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.
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.
Object detection systems usually employ bounding boxes, pixel resampling and application of high-quality classifiers. These approaches are heavy on computation and high on latency when it comes to real-time applications. Single shot detection, unlike other object detectors, doesn’t resample pixels or features for bounding boxes. Object Detection With SSD By eliminating the bounding boxes approach,…
The post What Is SSD & How It Improved Computer Vision Forever appeared first on Analytics India Magazine.
Object detection systems usually employ bounding boxes, pixel resampling and application of high-quality classifiers. These approaches are heavy on computation and high on latency when it comes to real-time applications. Single shot detection, unlike other object detectors, doesn’t resample pixels or features for bounding boxes. Object Detection With SSD By eliminating the bounding boxes approach,…
The post What Is SSD & How It Improved Computer Vision Forever appeared first on Analytics India Magazine.