Comparison of Object Detection Algorithms CNN, YOLO and SSD
Year: 2024
Type: article
Abstract: Since 2015, numerous studies have concentrated on object detection, a crucial element of computer vision, using convolutional neural networks (CNN) and their various architectures. Key methods for object detection done by “YOLO (You Only Look Once)”, “CNN”, and “SSD (Single Shot Multibox Detector)”. This paper explores three representative series of methods based on “CNN, YOLO, and SSD”, providing solutions to challenges like bounding box prediction in CNNs. The strength of these algorithms are measured in terms of accuracy, processing speed, and computational cost. YOLO models.we want to do comprehensive study of three models of object detection”(YOLO, CNN, SSD)”.
Author: Ghansham More, Omkar Patil, Omkar More, Mihir More, Samadhan Suryavanshi, Manisha Mali
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930780915
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