Machine learning is an expanding field with an ever-increasing role in everyday life, with its
utility in the industrial, agricultural, and medical sectors being undeniable. Recently, this …

Filter pruning is a technique that reduces computational complexity, inference time, and
memory footprint by removing unnecessary filters in convolutional neural networks (CNNs) …

In the field of object detection, deep learning has greatly improved accuracy compared to
previous algorithms and has been used widely in recent years. However, object detection …

Instance segmentation, which has been required in various applications in recent years, is
aimed at reliable bounding box (bbox) detection (ie, localization) and stable mask prediction …

This brief presents a dedicated FPGA implementation of the Gaussian TinyYOLOv3
accelerator using a streamline architecture for object detection in mobile and edge devices …

With the ease of accessing large unlabeled datasets, studies on semi-supervised learning
for object detection (SSOD) have become increasingly popular. Among these SSOD studies …

The success of research using convolutional neural network (CNN)-based camera sensor
processing for autonomous driving has accelerated the development of autonomous driving …

Channel pruning can efficiently reduce the computation and memory footprint within a
reasonable accuracy drop by removing unnecessary channels from convolutional neural …

Indoor human-carried object detection refers to the use of technologies and methods to
detect objects that may be carried by individuals in indoor environments. This can include …

Ambient Intelligence (AmI) encompasses technological infrastructures capable of sensing
data from environments and extracting high-level knowledge to detect or recognize users' …