Real Time Object Detection using Tensor Flow
Radhika Paturi, T. Bhavana, P.V.N. Sunandana, R. Srijyothi, S. Meghana
Abstract
Using today's technology, an item can be detected, located, and tracked using computer vision techniques like Object Detection with Tensor Flow. In the realm of computer imagining and foresight, object detection is closely linked. Photographs are intelligently interpreted in the same way as human imagination and foresight are. It distinguishes between images and objects rather than just detecting objects. Object detection frameworks including Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and faster RNN are revived and briefly introduced in this study (YOLO). After that, the recommended object detection architectures are reworked on. A little object is picked up by the traditional version when a picture is taken. A few tweaks are made to the current iteration. The ultimate outcome is nice and accurate, due to this strategy.