International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 185 - Number 7 |
Year of Publication: 2023 |
Authors: Shreyas Pagare, Rakesh Kumar |
10.5120/ijca2023922726 |
Shreyas Pagare, Rakesh Kumar . Object Detection Algorithms Compression CNN, YOLO and SSD. International Journal of Computer Applications. 185, 7 ( May 2023), 34-38. DOI=10.5120/ijca2023922726
Object detection is a crucial component of computer vision, and since 2015, several studies have expanded with the use of convolution neural networks and their changed structures. There are techniques for detecting representative objects, including YOLO and convolutional neural networks and also use SSD. This study introduces three exemplary CNN and YOLO-based and SSD algorithm series that address the CNN bounding box issue. We examine the accuracy, speed, and cost of many algorithmic series. All model of YOLO provides an excellent balance between speed and accuracy when compared to the most recent advanced solution.