Recent development in object detection are greatly driven by the success of region proposal approaches and region-based convolutional neural networks (R-CNNs). In this paper, we designed and implemented an object detection system using a faster-CNN method that shares full-image convolutional features with a detection network, so as to enable nearly cost-free region proposals. Development of this system is based on the previous work on Faster R-CNN. Results shows that with this method, we could achieve high accuracy while detecting objects.
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Design and Implementation of an Object Detection System Using Faster R-CNN
Semantic Scholar · Computer Science · 2019
Abstract
Recent development in object detection are greatly driven by the success of region proposal approaches and region-based convolutional neural networks (R-CNNs). In this paper, we designed and implemented an object detection system using a faster-CNN method that shares full-image convolutional features with a detection network, so as to enable nearly cost-free region proposals. Development of this system is based on the previous work on Faster R-CNN. Results shows that with this method, we could achieve high accuracy while detecting objects.