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Vincenzo Dentamaro, Donato Impedovo and Giuseppe Pirlo
Multiclass classification in cancer diagnostics, using DNA or Gene Expression Signatures, but also classification of bacteria species fingerprints in MALDI-TOF mass spectrometry data, is challenging because of imbalanced data and the high number of dimen...
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Md. Khaliluzzaman, Md. Abu Bakar Siddiq Sayem, Lutful KaderMisbah
Pág. 357 - 376
Human Activity Recognition (HAR), a vast area of a computer vision research, has gained standings in recent years due to its applications in various fields. As human activity has diversification in action, interaction, and it embraces a large amount of d...
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Md. Khaliluzzaman, Md. Abu Bakar Siddiq Sayem, Lutful KaderMisbah
Pág. 357 - 376
Human Activity Recognition (HAR), a vast area of a computer vision research, has gained standings in recent years due to its applications in various fields. As human activity has diversification in action, interaction, and it embraces a large amount of d...
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Alexandre M. de Carvalho and Ronaldo C. Prati
One of the significant challenges in machine learning is the classification of imbalanced data. In many situations, standard classifiers cannot learn how to distinguish minority class examples from the others. Since many real problems are unbalanced, thi...
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Huaping Guo, Jun Zhou and Chang-An Wu
Classification of data with imbalanced class distribution has encountered a significant drawback by most conventional classification learning methods which assume a relatively balanced class distribution. This paper proposes a novel classification method...
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Hansol Park, Kookjin Kim, Dongil Shin and Dongkyoo Shin
Recent advances in the Internet and digital technology have brought a wide variety of activities into cyberspace, but they have also brought a surge in cyberattacks, making it more important than ever to detect and prevent cyberattacks. In this study, a ...
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Matin Mortaheb, Cemil Vahapoglu and Sennur Ulukus
Multi-task learning (MTL) is a paradigm to learn multiple tasks simultaneously by utilizing a shared network, in which a distinct header network is further tailored for fine-tuning for each distinct task. Personalized federated learning (PFL) can be achi...
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Hong-Chan Chang, Yi-Che Wang, Yu-Yang Shih and Cheng-Chien Kuo
A homemade defective model of an induction motor was created by the laboratory team to acquire the vibration acceleration signals of five operating states of an induction motor under different loads. Two major learning models, namely a deep convolutional...
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Shenming Qu, Huafei Zhou, Bo Zhang and Shengbin Liang
Extracting roads from remote sensing images can support a range of geo-information applications. However, it is challenging due to factors such as the complex distribution of ground objects and occlusion of buildings, trees, shadows, etc. Pixel-wise clas...
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