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In recent times, learning-based methods for video deraining have demonstrated commendable results. However, there are two critical challenges that these methods are yet to address: exploiting temporal correlations among adjacent frames and ...

• We introduce a novel video deraining paradigm, alignment-shift-fusion.
• Constructing a large-scale rainy video dataset, LArge-scale RAiny Video Dataset.
• Establishing a correspondence between the synthetic and real-world domains.

Orthogonal Matching Pursuit (OMP) has been a powerful method in sparse signal recovery and approximation. However, OMP suffers computational issues when the signal has a large number of non-zeros. This paper advances OMP and its extension called ...

"The previous era was about information at your fingertips; I think of the AI era as expertise at your fingertips." - Satya Nadella, CNBC

This tutorial explores Large Language Model (LLM)-based autonomous agents, addressing the lack of comprehensive ...

Computing in the Network (COIN) has the potential to reduce the data traffic and thus the end-to-end latencies for data-rich services. Existing COIN studies have neglected the impact of the size of the data unit that the network nodes compute on. However, ...

Large Language Models (LLMs) have revolutionized the field of Natural Language Generation (NLG) by demonstrating an impressive ability to generate human-like text. However, their widespread usage introduces challenges that necessitate thoughtful ...

Pedestrian re-identification is a technique to locate the same individual in data from different cameras. Currently, the method of multi-source domain adaptation for pedestrian re-identification is becoming popular. In this approach, the core challenge ...

Video conferencing applications (VCAs) have become an indispensable tool for business, educational, and personal communications. There is, therefore, considerable interest in understanding and measuring the Quality of Experience (QoE) delivered by VCAs ...

The identification of compound-protein interactions (CPIs) plays a vital role in drug discovery. However, the huge cost and labor-intensive nature in vitro and vivo experiments make it urgent for researchers to develop novel CPI prediction ...

• We propose a novel cross multi-head attention oriented bidirectional interpretable CPI prediction model.
• The cross multi-head attention module of the proposed model integrates two multi-head scaled dot-product attentions, facilitating ...

In the study of unsupervised domain adaptation for pedestrian re-identification, one prevalent approach during training on unlabeled target domains involves generating pseudo-labels. However, due to the inability to guarantee the correctness of pseudo-...

• In this paper, we consider the problem of adaptive detection for distributed targets in zero-mean Gaussian clutter with unknown persymmetric covariance ...

In this paper, we consider the problem of adaptive detection for distributed targets in zero-mean Gaussian clutter with unknown persymmetric covariance matrix. The target signal is assumed to locate in a known subspace with unknown ...

The purpose of this paper is to research and experiment polyhededral model algorithm on the LoongArch64 architecture. In order to reduce the burden on programmers and adapt to the development of parallel programs on the Loongson multi-core chip, using ...

In the field of quantitative trading, it is common practice to transform raw historical stock data into indicative signals for the market trend. Such signals are called alpha factors. Alphas in formula forms are more interpretable and thus favored by ...

Video Conferencing Applications (VCAs) that support remote work and education have increased in use over the last two years, contributing to Internet bandwidth usage. VCA clients transmit video and audio to each other in peer-to-peer mode or ...

Constrained Reinforcement Learning (CRL) burgeons broad interest in recent years, which pursues maximizing long-term returns while constraining costs. Although CRL can be cast as a multi-objective optimization problem, it is still facing the key challenge ...

6G is believed to go beyond communication and provide integrated sensing and computing capabilities for a vision of Connected Intelligence with everything connected, everything sensed, and everything intelligent. Integrated sensing and ...

Recently, with the development of intelligent technology, the perception of low-light scenes has been gaining widespread attention. However, existing techniques usually focus on only one task (e.g., enhancement) and lose sight of the others (e.g., ...

In this paper, adaptive signal detection is addressed for range-spread targets in unknown zero-mean Gaussian clutter with persymmetric covariance matrix. The range-spread target can be expressed as the product of a known subspace and ...

Deep learning has revolutionized many machine learning tasks in recent years. Successful applications range from computer vision, natural language processing to speech recognition, etc. The success is partially due to the availability of large ...

Miner malware has been steadily increasing in recent years as the value of cryptocurrency rises, which poses a considerable threat to users’ device security. Miner malware has obvious behavior patterns in order to participate in blockchain computing. ...