Spoken keyword spotting (KWS) deals with the identification of keywords in audio streams
and has become a fast-growing technology thanks to the paradigm shift introduced by deep …

At present, with the advance of satellite image processing technology, remote sensing
images are becoming more widely used in real scenes. However, due to the limitations of …

Although vision transformers (ViTs) have achieved great success in computer vision, the
heavy computational cost hampers their applications to dense prediction tasks such as …

Abstract We present Mobile-Former, a parallel design of MobileNet and transformer with a
two-way bridge in between. This structure leverages the advantages of MobileNet at local …

Abstract Spiking Neural Networks (SNNs) have emerged as a biology-inspired method
mimicking the spiking nature of brain neurons. This bio-mimicry derives SNNs' energy …

Deep neural networks have been applied in many applications exhibiting extraordinary
abilities in the field of computer vision. However, complex network architectures challenge …

Detecting COVID-19 early may help in devising an appropriate treatment plan and disease
containment decisions. In this study, we demonstrate how transfer learning from deep …

In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental
Microorganism (EM) image segmentation task to assist microbiologists in detecting and …

Deploying convolutional neural networks (CNNs) on mobile devices is difficult due to the
limited memory and computation resources. We aim to design efficient neural networks for …

Abstract Binary Neural Network (BNN) shows its predominance in reducing the complexity of
deep neural networks. However, it suffers severe performance degradation. One of the …