Zobrazeno 1 - 10
of 1 505
pro vyhledávání: '"Mixture of Experts"'
Autor:
Neel Kanwal, Farbod Khoraminia, Umay Kiraz, Andrés Mosquera-Zamudio, Carlos Monteagudo, Emiel A. M. Janssen, Tahlita C. M. Zuiverloon, Chunming Rong, Kjersti Engan
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-25 (2024)
Abstract Background Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures resul
Externí odkaz:
https://doaj.org/article/d83437ab55034d4695f7d414d324e162
Publikováno v:
Alexandria Engineering Journal, Vol 110, Iss , Pp 557-566 (2025)
Accurate nuclei segmentation is essential for extracting quantitative information from histology images to support disease diagnosis and treatment decisions. However, precise segmentation is challenging due to the presence of clustered nuclei, varied
Externí odkaz:
https://doaj.org/article/5932682b35c24d3ab205a54c17adc7b7
Publikováno v:
Engineering Access, Vol 10, Iss 2, Pp 154-165 (2024)
Ensemble Learning is gaining traction in Reinforcement Learning (RL) due to its ability to improve performance, robustness, and capabilities of RL models. This paper addresses the challenge of production planning with fluctuating demand by proposing
Externí odkaz:
https://doaj.org/article/11bc884d136a40cab4cdda44f3262390
Autor:
Noriaki Hashimoto, Hiroyuki Hanada, Hiroaki Miyoshi, Miharu Nagaishi, Kensaku Sato, Hidekata Hontani, Koichi Ohshima, Ichiro Takeuchi
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100359- (2024)
In this study, we present a deep-learning-based multimodal classification method for lymphoma diagnosis in digital pathology, which utilizes a whole slide image (WSI) as the primary image data and flow cytometry (FCM) data as auxiliary information. I
Externí odkaz:
https://doaj.org/article/9d5f8550a204454c965758cbe4462f42
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Accurate line parameters are critical for and dispatch in distribution systems. External operating condition variations affect line parameters, reducing the accuracy of state estimation and power flow calculations. While many methods have been propos
Externí odkaz:
https://doaj.org/article/6104310c080d40e3a0bbe1881de68d97
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-37 (2024)
Abstract In this paper, a framework based on a sparse Mixture of Experts (MoE) architecture is proposed for the federated learning and application of a distributed classification model in domains (like cybersecurity and healthcare) where different pa
Externí odkaz:
https://doaj.org/article/b7074f2d85ca446e9dfcc30bd2b80274
Publikováno v:
IEEE Access, Vol 12, Pp 172358-172367 (2024)
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that requires accurate diagnosis and management, especially in long-term cardiac monitoring (LTCM) scenarios. Although ECG signal morphology can vary between patients and over time, tradition
Externí odkaz:
https://doaj.org/article/4e266bf8e3a04654aae87b00945b365e
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 11, p 151 (2024)
Credit card fraud detection is a critical challenge in the financial sector due to the rapidly evolving tactics of fraudsters and the significant class imbalance betweenegitimate and fraudulent transactions. Traditional models, while effective to som
Externí odkaz:
https://doaj.org/article/9705da76d0c54a43a025e508915469e3
Autor:
Baiwen Zhang, Meng Xu, Qing Wu, Sicheng Ye, Ying Zhang, Zufei Li, for the Alzheimer’s Disease Neuroimaging Initiative
Publikováno v:
Frontiers in Aging Neuroscience, Vol 16 (2024)
IntroductionMild cognitive impairment (MCI) is an important stage in Alzheimer’s disease (AD) research, focusing on early pathogenic factors and mechanisms. Examining MCI patient subtypes and identifying their cognitive and neuropathological patter
Externí odkaz:
https://doaj.org/article/88277fa6b45141de9e5ea6bbef94c7b4
Autor:
Ming Liu, Yanbing Liu, Weiyou Shi, Yitai Lou, Yuan Sun, Qi Meng, Dezheng Wang, Fangzhou Xu, Yang Zhang, Lei Zhang, Jiancai Leng
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionTransformer network is widely emphasized and studied relying on its excellent performance. The self-attention mechanism finds a good solution for feature coding among multiple channels of electroencephalography (EEG) signals. However, usi
Externí odkaz:
https://doaj.org/article/62574a4f7aa245f79ddb6d5f242347ed