|
|
|
|
|
Abdelghani Azri, Adil Haddi and Hakim Allali
Collaborative filtering (CF), a fundamental technique in personalized Recommender Systems, operates by leveraging user?item preference interactions. Matrix factorization remains one of the most prevalent CF-based methods. However, recent advancements in ...
ver más
|
|
|
|
|
|
|
|
|
Haohao Guo, Tianxiang Xiang, Yancheng Liu, Qiaofen Zhang, Yi Wei and Fengkui Zhang
This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as th...
ver más
|
|
|
|
|
|
|
|
|
Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
ver más
|
|
|
|
|
|
|
|
|
Juan Luis Pérez-Ruiz, Yu Tang, Igor Loboda and Luis Angel Miró-Zárate
In the field of aircraft engine diagnostics, many advanced algorithms have been proposed over the last few years. However, there is still wide room for improvement, especially in the development of more integrated and complete engine health management sy...
ver más
|
|
|
|
|
|
|
|
|
Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
ver más
|
|
|
|