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

One-shot image semantic segmentation poses a challenging task of recognizing the object
regions from unseen categories with only one annotated example as supervision. In this …

Filter pruning has been widely applied to neural network compression and acceleration.
Existing methods usually utilize pre-defined pruning criteria, such as Lp-norm, to prune …

Neuron-level structured pruning is a very effective technique to reduce the computation of
neural networks without compromising prediction accuracy. In previous works, structured …

Runtime and memory consumption are two important aspects for efficient image super-
resolution (EISR) models to be deployed on resource-constrained devices. Recent …

Abstract Artificial Intelligence of Things (AIoT) which integrates artificial intelligence (AI) and
the Internet of Things (IoT), has attracted increasing attention recently. With the remarkable …

When a natural disaster occurs, the most critical task is to search and rescue trapped people
as soon as possible. In recent years, unmanned aerial vehicles (UAVs) have been widely …

Pruning, the task of sparsifying deep neural networks, received increasing attention recently.
Although state-of-the-art pruning methods extract highly sparse models, they neglect two …

Convolutional neural network (CNN) models have recently demonstrated impressive
performance in medical image analysis. However, there is no clear understanding of why …

Because of its simple network structure and efficient learning mode, the Broad Learning
System (BLS) has achieved impressive performance in image classification tasks …