Zobrazeno 1 - 10
of 1 306
pro vyhledávání: '"Triplet loss"'
Publikováno v:
Acta Informatica Pragensia, Vol 13, Iss 2, Pp 234-250 (2024)
Person identification through chest X-ray radiographs stands as a vanguard in both healthcare and biometrical security domains. In contrast to traditional biometric modalities, such as facial recognition, fingerprints and iris scans, the research ori
Externí odkaz:
https://doaj.org/article/aabc4a4b235b4956aea5f01652fc53fd
Publikováno v:
Ecosphere, Vol 15, Iss 10, Pp n/a-n/a (2024)
Abstract Estimating the size of animal populations plays an important role in evidence‐based conservation and management. Some methods for estimating population size rely on animals being individually identifiable. Traditionally, this has been done
Externí odkaz:
https://doaj.org/article/62674aef3f1b4d47b986d54a625ce93c
Publikováno v:
IEEE Access, Vol 12, Pp 66801-66808 (2024)
This study addresses the persistent challenge of in-vehicle noise, a significant factor affecting customer satisfaction and safety in the automotive industry. Despite advancements in understanding various noise sources and mitigation strategies, vehi
Externí odkaz:
https://doaj.org/article/cd279119e62345bf95e61414616ed33e
Autor:
Raoof Altaher, Hakan Koyuncu
Publikováno v:
Mathematics, Vol 12, Iss 18, p 2919 (2024)
In the rapidly evolving field of biometric authentication, deep learning has become a cornerstone technology for face detection and recognition tasks. However, traditional optimizers often struggle with challenges such as overfitting, slow convergenc
Externí odkaz:
https://doaj.org/article/8ce5c59e9a624aaca83694df94791987
Autor:
Alaa Alnissany, Yazan Dayoub
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-12 (2023)
Abstract Person Re-identification (ReID) is the process of matching target individuals to their images within different images or videos captured from a variety of angles or cameras. This is a critical task for surveillance applications, in particula
Externí odkaz:
https://doaj.org/article/2ae73adbb131441a87433597660810ee
Autor:
Li Chunguang
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Migration learning is a kind of deep learning that plays an important role in risk prediction and warning. In this paper, we use the Triplet-loss representation learning technique to map data samples of the same category to adjacent spatial regions,
Externí odkaz:
https://doaj.org/article/a8074ae018c346a4ab80e9674e0e1521
Autor:
Ngoc D. Le, Nhung T. H. Nguyen
Publikováno v:
Frontiers in Research Metrics and Analytics, Vol 8 (2023)
Biomedical entity linking task is the task of mapping mention(s) that occur in a particular textual context to a unique concept or entity in a knowledge base, e.g., the Unified Medical Language System (UMLS). One of the most challenging aspects of th
Externí odkaz:
https://doaj.org/article/8da68e425f8c4a08b6da763e94145065
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 5, Pp 5049-5062 (2023)
Abstract Recently, graph contrastive learning (GCL) has achieved remarkable performance in graph representation learning. However, existing GCL methods usually follow a dual-channel encoder network (i.e., Siamese networks), which adds to the complexi
Externí odkaz:
https://doaj.org/article/7a684ff7b1034a2c956fc4c5ed0a7175
Autor:
Faizal Hajamohideen, Noushath Shaffi, Mufti Mahmud, Karthikeyan Subramanian, Arwa Al Sariri, Viswan Vimbi, Abdelhamid Abdesselam, for the Alzheimer’s Disease Neuroimaging Initiative
Publikováno v:
Brain Informatics, Vol 10, Iss 1, Pp 1-13 (2023)
Abstract Alzheimer’s disease (AD) is a neurodegenerative disease that causes irreversible damage to several brain regions, including the hippocampus causing impairment in cognition, function, and behaviour. Early diagnosis of the disease will reduc
Externí odkaz:
https://doaj.org/article/d5c2b1b382cf4ad398536223547e5c3a
Autor:
Jaesub Yun, Jong-Seok Lee
Publikováno v:
IEEE Access, Vol 11, Pp 31467-31478 (2023)
The imbalance of classes in real-world datasets poses a major challenge in machine learning and classification, and traditional synthetic data generation methods often fail to address this problem effectively. A major limitation of these methods is t
Externí odkaz:
https://doaj.org/article/266d3b180b9c4ce1bbf19261b1bcf136