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In this issue, “Best of the Web” presents the modified National Institute of Standards and Technology (MNIST) resources, consisting of a collection of handwritten digit images used extensively in ...
Generative artificial intelligence can make powerful artifacts when used at scale, but developing trust in these artifacts and controlling their creation are es ...
Underwater images encounter a range of quality degradation issues caused by the differential scattering and absorption of light in water. To address these challenges, we introduce a WFAC method, a ...
In real-world applications, screen capturing represents a significant scenario where this process can induce substantial distortion to the original image. Previous methods for simulating ...
Dynamic stream learning, which emphasizes high-velocity, single-pass, real-time responses to arriving data, is revealing new challenges to the standard machine learning paradigm. In particular, ...
In this study, we propose Multimodal Fusion-supervised Cross-modality Alignment Perception (MulFS-CAP), a novel framework for single-stage fusion of unregistered infrared-visible images. Traditional ...
Hyperspectral image (HSI) classification has been extensively studied in the context of Earth observation. However, its application in Mars exploration remains limited. Although convolutional neural ...
Pavement defects such as cracks, net cracks, and pit slots can cause potential traffic safety problems. The timely detection and identification play a key role in reducing the harm of various pavement ...
Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series analytics is ...
What will Wi-Fi 8 be? Driven by the strict requirements of emerging applications, next-generation Wi-Fi is set to prioritize ultra high reliability (UHR) above all. In this article, we explore the ...
Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous vehicles (AVs) ...
Cluster analysis plays an indispensable role in machine learning and data mining. Learning a good data representation is crucial for clustering algorithms. Recently, deep clustering (DC), which can ...
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