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Iqbal Muhammad Zubair, Yung-Seop Lee and Byunghoon Kim
The selection of group features is a critical aspect in reducing model complexity by choosing the most essential group features, while eliminating the less significant ones. The existing group feature selection methods select a set of important group fea...
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Saima Bhatti, Asif Ali Shaikh, Asif Mansoor and Murtaza Hussain
Machinery components undergo wear and tear over time due to regular usage, necessitating the establishment of a robust prognosis framework to enhance machinery health and avert catastrophic failures. This study focuses on the collection and analysis of v...
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Wenbo Peng and Jinjie Huang
Current object detection methods typically focus on addressing the distribution discrepancies between source and target domains. However, solely concentrating on this aspect may lead to overlooking the inherent limitations of the samples themselves. This...
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Jingxiong Lei, Xuzhi Liu, Haolang Yang, Zeyu Zeng and Jun Feng
High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate back...
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Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira and Alisson Assis Cardoso
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
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