In recent years there has been remarkable progress in one computer vision application
area: object detection. One of the most challenging and fundamental problems in object …

To improve the recognition model accuracy of crop disease leaves and locating diseased
leaves, this paper proposes an improved Faster RCNN to detect healthy tomato leaves and …

On the road to making self-driving cars a reality, academic and industrial researchers are
working hard to continue to increase safety while meeting technical and regulatory …

The article presents integration process of convolution and batch normalization layer for
further implementation on FPGA. The convolution kernel is binarized and merged with batch …

Standard classification tasks have already achieved good results in computer vision.
However, the task of Architectural style classification yet faces many challenges, since the …

Object detection from RGB images is a long-standing problem in image processing and
computer vision. It has applications in various domains including robotics, surveillance …

Additive manufacturing (AM) has gained increasing attention over the past years due to its
fast prototype, easier modification, and possibility for complex internal texture devices when …

Abstract Convolution Neural Networks are now widely used in image processing, object
detection, video detection, and other classification tasks. Thus the acceleration of CNN is …

Object location is a crucial computer vision method often used as a previous stage to object
classification. Object-location algorithms require high computational and memory resources …

This paper focuses on the power efficient design on the FPGA SoC for the object detection
system based on Binary Convolutional Neural Network (BCNN). Especially, for the small IoT …