Zobrazeno 1 - 10 of 14 pro vyhledávání: '"Ranpreet Kaur"'
1
Akademický článek
Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images
Autor: Ranpreet Kaur, Hamid GholamHosseini, Roopak Sinha, Maria Lindén
Publikováno v: BMC Medical Imaging, Vol 22, Iss 1, Pp 1-13 (2022)
Abstract Background Melanoma is the most dangerous and aggressive form among skin cancers, exhibiting a high mortality rate worldwide. Biopsy and histopathological analysis are standard procedures for skin cancer detection and prevention in clinical
Externí odkaz: https://doaj.org/article/13188c8c9bb84f209cbfff8019883040
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2
Akademický článek
Melanoma Classification Using a Novel Deep Convolutional Neural Network with Dermoscopic Images
Autor: Ranpreet Kaur, Hamid GholamHosseini, Roopak Sinha, Maria Lindén
Publikováno v: Sensors, Vol 22, Iss 3, p 1134 (2022)
Automatic melanoma detection from dermoscopic skin samples is a very challenging task. However, using a deep learning approach as a machine vision tool can overcome some challenges. This research proposes an automated melanoma classifier based on a d
Externí odkaz: https://doaj.org/article/0ad6f688ff344d0eb66220965087e2be
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5
From machine learning to deep learning: experimental comparison of machine learning and deep learning for skin cancer image segmentation
Autor: Ranpreet Kaur
Publikováno v: Rangahau Aranga: AUT Graduate Review. 1
Skin lesion analysis is a tedious and challenging task, thus, in this research the suitability of employing machine learning or deep learning approaches for automatic lesion segmentation on dermoscopic skin cancer images is determined. The segmented
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e6ac5825f018e0dd1dbb7bc27171d54d
https://doi.org/10.24135/rangahau-aranga.v1i1.32
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9
Automatic Lesion Segmentation Using Atrous Convolutional Deep Neural Networks in Dermoscopic Skin Cancer Images
Autor: Hamid GholamHosseini, Ranpreet Kaur, Roopak Sinha
Background: Among skin cancers, melanoma is the most dangerous and aggressive form, exhibiting a high mortality rate worldwide. Biopsy and histopatholog-ical analysis are common procedures for skin cancer detection and prevention in clinical settings
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::568076deb021aeb94c98bffc327b185b
https://doi.org/10.21203/rs.3.rs-285138/v1
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10
Deep Learning in Medical Applications: Lesion Segmentation in Skin Cancer Images Using Modified and Improved Encoder-Decoder Architecture
Autor: Ranpreet Kaur, Hamid GholamHosseini, Roopak Sinha
Publikováno v: Communications in Computer and Information Science ISBN: 9783030720728
The rise of deep learning techniques, such as a convolutional neural network (CNN) in solving medical image problems, offered fascinating results that motivated researchers to design automatic diagnostic systems. Image segmentation is one of the cruc
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5b704f31de86f5efdcf07cab2a9b6f7c
https://doi.org/10.1007/978-3-030-72073-5_4
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