Target detection is a hard real-time task for video and image processing. This task has
recently been accomplished through the feedforward process of convolutional neural …

In recent years, convolutional neural networks (CNNs) have demonstrated their ability to
solve problems in many fields and with accuracy that was not possible before. However, this …

Deep learning, the fastest growing segment of Artificial Neural Network (ANN), has led to the
emergence of many machine learning applications and their implementation across multiple …

Image classification is known to be one of the most challenging problems in the domain of
computer vision. Significant research is being done on developing systems and algorithms …

Object detection remains an active area of research in the field of computer vision, and
considerable advances and successes has been achieved in this area through the design of …

Convolutional neural networks (CNNs) have had great success when applied to computer
vision technology, and many application-specific integrated circuit (ASIC) and field …

Tiny machine learning (TinyML) has become an emerging field according to the rapid
growth in the area of the internet of things (IoT). However, most deep learning algorithms are …

In recent years, convolutional neural network (CNN)-based algorithms have been widely
used in remote sensing image processing and show tremendous performance in a variety of …

We implement the YOLO (You only look once) object detector on an FPGA, which is faster
and has higher accuracy. It is based on the convolutional deep neural network (CNN), and it …

Convolutional neural network (CNN)-based object detection has been widely employed in
various applications such as autonomous driving and intelligent video surveillance …