Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …

The remarkable capabilities and intricate nature of Artificial Intelligence (AI) have
dramatically escalated the imperative for specialized AI accelerators. Nonetheless …

The success of deep learning in visual recognition tasks has driven advancements in
multiple fields of research. Particularly, increasing attention has been drawn towards its …

High-level synthesis (HLS) has been widely adopted as it significantly improves the
hardware design productivity and enables efficient design space exploration (DSE). Existing …

Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

Object detection and tracking (ODT) is a crucial research area in video surveillance (VS)
systems and poses a significant challenge in computer vision and image processing. The …

High quality AI solutions require joint optimization of AI algorithms and their hardware
implementations. In this work, we are the first to propose a fully simultaneous, Efficient …

Existing FPGA-based DNN accelerators typically fall into two design paradigms. Either they
adopt a generic reusable architecture to support different DNN networks but leave some …

Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a growing demand for
domain-specific hardware accelerators (ie, DNN chips). However, designing DNN chips is …