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pro vyhledávání: '"DING Weiping"'
Accurate cancer survival prediction is crucial for assisting clinical doctors in formulating treatment plans. Multimodal data, including histopathological images and genomic data, offer complementary and comprehensive information that can greatly enh
Externí odkaz:
http://arxiv.org/abs/2408.04170
The twin support vector machine (TWSVM) classifier has attracted increasing attention because of its low computational complexity. However, its performance tends to degrade when samples are affected by noise. The granular-ball fuzzy support vector ma
Externí odkaz:
http://arxiv.org/abs/2408.00699
Publikováno v:
Information Fusion, 2024: 102540
In recent years, the denoising diffusion model has achieved remarkable success in image segmentation modeling. With its powerful nonlinear modeling capabilities and superior generalization performance, denoising diffusion models have gradually been a
Externí odkaz:
http://arxiv.org/abs/2408.02075
Publikováno v:
IEEE Transactions on Fuzzy Systems ( Early Access ) 2024
Histopathological image classification constitutes a pivotal task in computer-aided diagnostics. The precise identification and categorization of histopathological images are of paramount significance for early disease detection and treatment. In the
Externí odkaz:
http://arxiv.org/abs/2407.15312
Publikováno v:
IEEE Transactions on Fuzzy Systems 2024
Feature selection is a vital technique in machine learning, as it can reduce computational complexity, improve model performance, and mitigate the risk of overfitting. However, the increasing complexity and dimensionality of datasets pose significant
Externí odkaz:
http://arxiv.org/abs/2407.15893
The High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases. However, practical applica
Externí odkaz:
http://arxiv.org/abs/2407.11425
Federated Learning (FL) offers innovative solutions for privacy-preserving collaborative machine learning (ML). Despite its promising potential, FL is vulnerable to various attacks due to its distributed nature, affecting the entire life cycle of FL
Externí odkaz:
http://arxiv.org/abs/2407.06754
Active learning seeks to achieve strong performance with fewer training samples. It does this by iteratively asking an oracle to label new selected samples in a human-in-the-loop manner. This technique has gained increasing popularity due to its broa
Externí odkaz:
http://arxiv.org/abs/2405.00334
Autor:
Guan, Runwei, Hu, Rongsheng, Zhou, Zhuhao, Xue, Tianlang, Man, Ka Lok, Smith, Jeremy, Lim, Eng Gee, Ding, Weiping, Yue, Yutao
In reality, images often exhibit multiple degradations, such as rain and fog at night (triple degradations). However, in many cases, individuals may not want to remove all degradations, for instance, a blurry lens revealing a beautiful snowy landscap
Externí odkaz:
http://arxiv.org/abs/2404.10342
Publikováno v:
Information Fusion 2024
As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in parallel with the actual industrial processes to offer ``Human-Centric" Safe, Secure, Sustainable, Sensitive, Service, and Smartness ``6S" manufacturing solut
Externí odkaz:
http://arxiv.org/abs/2404.07476