The front deployed deep learning system is a promising technology for the next generation
of industrial applications, which can extract essential information from high dimension …

Abstract The Internet of Things (IoT), as an emerging technology that connects a wide range
of smart devices to the Internet, has significantly impacted our daily lives and will continue to …

In this paper, we discuss a general framework, namely Opportunistic Distributed Learning
(ODL), which allows any node in the network to initiate a learning task while …

This paper aims to describe a combined machine vision and deep learning method for
quality control in an industrial environment. The innovative approach used for the proposed …

This paper proposes an ultra-low-power hardware architecture of a tiny machine learning
(tinyML)-based conversion from Pulse Density Modulation (PDM) to Pulse Code Modulation …

The rapid evolution of Unmanned Aerial Vehicles (UAVs) has revolutionized target search
operations in various fields, including military applications, search and rescue missions, and …

This paper explores the integration and application of Approximate Computing (AxC)
approaches to Machine Learning (ML), especially Deep Learning (DL) models. We focus on …

Recently, the rapid advancement of AI technologies has witnessed the exceptional
performance of Deep Learning algorithms in diverse real-world challenges. Meanwhile, the …

요 약엣지 단말기의 경우 클라우드와 달리 연산/전력 등의 자원의 제약으로 연산량이 많은
다양한인공지능 모델을 활용하기 어렵다. 따라서 데이터 통신을 통해 클라우드와 엣지 …