Over the past decade, the dominance of deep learning has prevailed across various
domains of artificial intelligence, including natural language processing, computer vision …

Neural network sparsity has attracted many research interests due to its similarity to
biological schemes and high energy efficiency. However, existing methods depend on long …

Unmanned aerial vehicles (UAVs) have become an important tool for transmission line
inspection, and the inspection images taken by UAVs often contain complex backgrounds …

In recent years, more and more devices are connected to the network, generating an
overwhelming amount of data. This term that is booming today is known as the Internet of …

Advancements in artificial intelligence are leading researchers to find use cases that were
not as straightforward to solve in the past. The use case of simulated autonomous driving …

Network compression techniques that combine tensor decompositions and pruning have
shown promise in leveraging the advantages of both strategies. In this work, we propose …

In this paper, we present CORING, which is short for effiCient tensOr decomposition-based
filteR prunING, a novel filter pruning methodology for neural networks. CORING is crafted to …

Compared with the previous generation of High Efficiency Video Coding (HEVC), Versatile
Video Coding (VVC) introduces a quadtree and multi-type tree (QTMT) partition structure …

Surface defect detection is a critical task in industrial production, and numerous methods
have been proposed to achieve high detection accuracy. Although deep-learning-based …

One of the greatest engineering feats in history is the construction of tunnels, and the
management of tunnel safety depends heavily on the detection of tunnel defects. However …