An Optimized Object Detection System Using You Only Look Once Algorithm and Compare with Tiny-Yolo algorithm with Increased Accuracy
The proposed Novel You Only Look Once algorithm seems to be significantly better than the tiny-yolo algorithm at detecting, recognizing, and tracking with more accuracy.
Abstract
Aim: The Aim of the study is to use the Novel You Only Look Once Algorithm to track, fete variety of objects of varied sizes. Materials and Methods: Various Objects are detected and recognized and then tracked using the Novel You Only Look Once ($N=10$) and it's accuracy is compared using tiny-yolo ($N=10$). There are two groups that are analyzed. Results and Discussion: The tiny-yolo and the Novel You Only Look Once models are implemented in this study, and the accuracy of the algorithms are compared with a significance p value of 0.001. Conclusion: The proposed Novel You Only Look Once algorithm seems to be significantly better than the tiny-yolo algorithm at detecting, recognizing, and tracking with more accuracy.