Zobrazeno 1 - 10
of 2 409
pro vyhledávání: '"pixel labeling"'
In the realm of practical Anomaly Detection (AD) tasks, manual labeling of anomalous pixels proves to be a costly endeavor. Consequently, many AD methods are crafted as one-class classifiers, tailored for training sets completely devoid of anomalies,
Externí odkaz:
http://arxiv.org/abs/2407.03130
Autor:
Mohammed Alonazi, Asifa Mehmood Qureshi, Saud S. Alotaibi, Nouf Abdullah Almujally, Naif Al Mudawi, Abdulwahab Alazeb, Ahmad Jalal, Jaekwang Kim, Moohong Min
Publikováno v:
IEEE Access, Vol 11, Pp 80973-80985 (2023)
Autonomous vehicle detection and tracking are crucial for intelligent transportation management and control systems. Although many techniques are used to develop smart traffic systems, this article discusses vehicle detection and tracking using pixel
Externí odkaz:
https://doaj.org/article/cfad66a81bc749279c40dc2b61b19462
Autor:
Gare, Gautam Rajendrakumar, Schoenling, Andrew, Philip, Vipin, Tran, Hai V, deBoisblanc, Bennett P, Rodriguez, Ricardo Luis, Galeotti, John Michael
Publikováno v:
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1406-1410
We propose using a pre-trained segmentation model to perform diagnostic classification in order to achieve better generalization and interpretability, terming the technique reverse-transfer learning. We present an architecture to convert segmentation
Externí odkaz:
http://arxiv.org/abs/2201.10166
Autor:
Muhammad Ovais Yusuf, Muhammad Hanzla, Hameedur Rahman, Touseef Sadiq, Naif Al Mudawi, Nouf Abdullah Almujally, Asaad Algarni
Publikováno v:
IEEE Access, Vol 12, Pp 72896-72911 (2024)
Systems must be capable of detecting and tracking autonomous vehicles for intelligent management and control of transportation. Even though several methods are used to create intelligent systems for traffic monitoring, this article explains how to de
Externí odkaz:
https://doaj.org/article/ef9ef4ed2e87481289e80dbf1daa4736
Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-tr
Externí odkaz:
http://arxiv.org/abs/2005.13363
Akademický článek
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Akademický článek
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While there has been significant progress in solving the problems of image pixel labeling, object detection and scene classification, existing approaches normally address them separately. In this paper, we propose to tackle these problems from a bott
Externí odkaz:
http://arxiv.org/abs/1807.07284
Autor:
Kong, Shu, Fowlkes, Charless
To achieve parsimonious inference in per-pixel labeling tasks with a limited computational budget, we propose a \emph{Pixel-wise Attentional Gating} unit (\emph{PAG}) that learns to selectively process a subset of spatial locations at each layer of a
Externí odkaz:
http://arxiv.org/abs/1805.01556
Autor:
Maroua Mehri, Ramzi Chaieb, Karim Kalti, Pierre Héroux, Rémy Mullot, Najoua Essoukri Ben Amara
Publikováno v:
Journal of Imaging, Vol 4, Iss 8, p 97 (2018)
Recently, texture features have been widely used for historical document image analysis. However, few studies have focused exclusively on feature selection algorithms for historical document image analysis. Indeed, an important need has emerged to us
Externí odkaz:
https://doaj.org/article/995aee0fa9bb4ce8aee2e2deff64564a