Zobrazeno 1 - 10
of 2 289
pro vyhledávání: '"Self training"'
Publikováno v:
IEEE Access, Vol 12, Pp 110418-110431 (2024)
In the real world, there are only a small amount of data with labels. To make full use of the potential structural information of unlabeled data to train a better classifier, researchers have proposed many semi-supervised learning algorithms. Among t
Externí odkaz:
https://doaj.org/article/96ad1915e58b4ea8880166c48aa568f5
Autor:
Michela Venturini, Fateme Nateghi Haredasht, Frantisek Sabovcik, Robert J. H. Miller, Tatiana Kuznetsova, Celine Vens
Publikováno v:
IEEE Access, Vol 12, Pp 89754-89762 (2024)
Heart transplantation is a life-saving procedure for children affected by end-stage heart failure. However, despite recent improvements in long-term outcomes, 1-year post-transplantation mortality has remained relatively high. Accurate prediction of
Externí odkaz:
https://doaj.org/article/7539fd68637149e0a05d4fb4be5fe21c
Autor:
Xi Tang, Dongchen Jiang
Publikováno v:
IEEE Access, Vol 12, Pp 59893-59900 (2024)
Named entity recognition is a key prerequisite for many tasks. However, the high cost of entity annotation limits feature learning and generalization capabilities of models. To address this problem, this paper integrates the weakly supervised method
Externí odkaz:
https://doaj.org/article/1e8fd3efbb404441adf8c79b7bde38c6
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 2, Pp 2366-2384 (2024)
In this paper, we introduce a novel deep learning method for dental panoramic image segmentation, which is crucial in oral medicine and orthodontics for accurate diagnosis and treatment planning. Traditional methods often fail to effectively combine
Externí odkaz:
https://doaj.org/article/8ec6ab8fd6bb404fbd2d3a10c34058f3
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2272-2282 (2024)
Change detection (CD) using deep learning techniques is a prominent topic in the field of remote sensing (RS). However, the existing methods require large amounts of labeled samples for supervised learning, which is time-consuming and labor-intensive
Externí odkaz:
https://doaj.org/article/364f1878b3284833aceec2b197ec74d1
Publikováno v:
ETRI Journal, Vol 45, Iss 6, Pp 1007-1021 (2023)
Stroke is the leading cause of permanent disability in adults, and it can cause permanent brain damage. According to the World Health Organization, 795,000 Americans experience a new or recurrent stroke each year. Early detection of medical disorders
Externí odkaz:
https://doaj.org/article/37fa72ae74ba4745af3a49512402d62e
Publikováno v:
Mathematics, Vol 12, Iss 15, p 2415 (2024)
With increasing wafer sizes and diversifying die patterns, automated optical inspection (AOI) is progressively replacing traditional visual inspection (VI) for wafer defect detection. Yet, the defect classification efficacy of current AOI systems in
Externí odkaz:
https://doaj.org/article/705c3169b938471caa773306cde27e00
Publikováno v:
Sensors, Vol 24, Iss 15, p 5060 (2024)
Side-scan sonar is a principal technique for subsea target detection, where the quantity of sonar images of seabed targets significantly influences the accuracy of intelligent target recognition. To expand the number of representative side-scan sonar
Externí odkaz:
https://doaj.org/article/f99abb3d9ba849549e3795754bae49d0
Publikováno v:
Mathematics, Vol 12, Iss 15, p 2348 (2024)
Semi-supervised object detection helps to monitor and manage maritime transportation effectively, saving labeling costs. Currently, many semi-supervised object detection methods use a combination of data augmentation and pseudo-label to improve model
Externí odkaz:
https://doaj.org/article/86cd0fe5394e4596a0838ff94dffc10c
Publikováno v:
Applied Sciences, Vol 14, Iss 14, p 6295 (2024)
Stroke causes disability and significantly affects patient quality of life. Post-stroke rehabilitation of upper limb function is crucial, as it affects daily activities and individual autonomy. Traditional rehabilitation methods often require frequen
Externí odkaz:
https://doaj.org/article/b8d570199d084ae69bf1abf71dd5617c