This study concentrates on deep learning-based lightweight object detection models on
edge devices. Designing such lightweight object recognition models is more difficult than …

Object detection is one of the basic tasks and research hotspots in the field of computer
vision. The YOLO (You Only Look Once) frames object detection is a regression problem to …

The breakthrough of deep learning has started a technological revolution in various areas
such as object identification, image/video recognition and semantic segmentation. Neural …

In recent years, convolutional neural networks (CNNs) have become widely adopted for
computer vision tasks. Field-programmable gate arrays (FPGAs) have been adequately …

Abstract Generative Adversarial Networks (GANs) have achieved huge success in
generating high-fidelity images, however, they suffer from low efficiency due to tremendous …

Convolutional neural network (CNN) based object detection algorithms are becoming
dominant in many application fields due to their superior accuracy advantage over …

Convolutional neural networks (CNNs) require both intensive computation and frequent
memory access, which lead to a low processing speed and large power dissipation …

Sparse-Matrix Dense-Matrix multiplication (SpMM) is the key operator for a wide range of
applications including scientific computing, graph processing, and deep learning …

The revolution of machine learning poses an unprecedented demand for computation
resources, urging more transistors on a single monolithic chip, which is not sustainable in …

Modern machine learning (ML) applications are often deployed in the cloud environment to
exploit the computational power of clusters. However, this in-cloud computing scheme …