Zobrazeno 1 - 10
of 453
pro vyhledávání: '"convolutional auto-encoder"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-22 (2024)
Abstract Background Long non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations. Results In this paper, we propose a p
Externí odkaz:
https://doaj.org/article/e13ac069253f423d91b6a59442be05b0
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Maintaining consistent and accurate temperature is critical for the safe and effective storage of vaccines. Traditional monitoring methods often lack real-time capabilities and may not be sensitive enough to detect subtle anomalies. This paper presen
Externí odkaz:
https://doaj.org/article/a4f225d97ea2460e9a60c34d207d4a21
Autor:
Ankit Shukla, Avinash Upadhyay, Manoj Sharma, Anil Saini, Nuzhat Fatema, Hasmat Malik, Asyraf Afthanorhan, Mohammad Asef Hossaini
Publikováno v:
IEEE Access, Vol 12, Pp 123969-123984 (2024)
Super-resolution (SR) of the degraded and real low-resolution (LR) video remains a challenging problem despite the development of deep learning-based SR models. Most existing state-of-the-art networks focus on getting high-resolution (HR) videos from
Externí odkaz:
https://doaj.org/article/995b7a12c61c44d7bad2911acf3775a0
Publikováno v:
Machines, Vol 12, Iss 6, p 362 (2024)
As one of the most important components in rotating machinery, if bearings fail, serious disasters may occur. Therefore, the remaining useful life (RUL) prediction of bearings is of great significance. Health indicator (HI) construction and early fau
Externí odkaz:
https://doaj.org/article/6094f349afcd41979b7d9d7f59d962c4
Publikováno v:
IEEE Access, Vol 11, Pp 143387-143401 (2023)
According to the Global Cancer Observatory, 2020, breast cancer is the most prevalent cancer type in both genders (11.7%), while prostate cancer is the second most common cancer type in men (14.1%). In digital pathology, Content-Based Medical Image R
Externí odkaz:
https://doaj.org/article/2da287ddeef94048b225795388bd2150
Publikováno v:
Protection and Control of Modern Power Systems, Vol 7, Iss 1, Pp 1-14 (2022)
Abstract Artificial intelligence (AI) can potentially improve the reliability of transformer protection by fusing multiple features. However, owing to the data scarcity of inrush current and internal fault, the existing methods face the problem of po
Externí odkaz:
https://doaj.org/article/4bc8f1189253444486f99c35602e2ba9
Publikováno v:
Remote Sensing, Vol 16, Iss 4, p 717 (2024)
With the development of artificial intelligence, the ability to capture the background characteristics of hyperspectral imagery (HSI) has improved, showing promising performance in hyperspectral anomaly detection (HAD) tasks. However, existing method
Externí odkaz:
https://doaj.org/article/ed89e4eec1a9457abde367d197a811a7
Akademický článek
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Akademický článek
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Autor:
Zahra Tabatabaei, Yuandou Wang, Adrián Colomer, Javier Oliver Moll, Zhiming Zhao, Valery Naranjo
Publikováno v:
Bioengineering, Vol 10, Iss 10, p 1144 (2023)
The paper proposes a federated content-based medical image retrieval (FedCBMIR) tool that utilizes federated learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. CBMIR is a tool to find the most s
Externí odkaz:
https://doaj.org/article/f74cf3ed35414f359e318f195a5f403f