Výsledky vyhledávání - "Syeda Furruka Banu"

Akademický článek

Recognizing Food Places in Egocentric Photo-Streams Using Multi-Scale Atrous Convolutional Networks and Self-Attention Mechanism

Autor: Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Farhan Akram, Estefania Talavera, Syeda Furruka Banu, Petia Radeva, Domenec Puig

Publikováno v: IEEE Access, Vol 7, Pp 39069-39082 (2019)

Wearable sensors (e.g., lifelogging cameras) represent very useful tools to monitor people's daily habits and lifestyle. Wearable cameras are able to continuously capture different moments of the day of their wearers, their environment, and interacti

Externí odkaz: https://doaj.org/article/9123dc28b54940d4a3d62cbde83622b3

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Akademický článek

AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation

Autor: Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Domenec Puig, Hatem A. Raswan

Publikováno v: Applied Sciences, Vol 11, Iss 21, p 10132 (2021)

Lung cancer is a deadly cancer that causes millions of deaths every year around the world. Accurate lung nodule detection and segmentation in computed tomography (CT) images is a vital step for diagnosing lung cancer early. Most existing systems face

Externí odkaz: https://doaj.org/article/42f0b75d487e478abce7b0996cf5f2d4

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SLSNet: Skin lesion segmentation using a lightweight generativeadversarial network

Autor: Hatem A. Rashwan, Mohamed Abdel-Nasser, Kabir Ahmed Choudhury, Vivek Kumar Singh, Domenec Puig, Md. Mostafa Kamal Sarker, Petia Radeva, Sylvie Chambon, Forhad U H Chowdhury, Farhan Akram, Syeda Furruka Banu

Publikováno v: Dipòsit Digital de la UB
Universidad de Barcelona

The determination of precise skin lesion boundaries in dermoscopic images using automated methods faces many challenges, most importantly, the presence of hair, inconspicuous lesion edges and low contrast in dermoscopic images, and variability in the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f04f90fb2d8bb2bc5dd44261655158f4
http://hdl.handle.net/2445/184577

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WEU-Net: A Weight Excitation U-Net for Lung Nodule Segmentation

Autor: Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Hatem A. Rashwan, Domenec Puig

Lung cancer is a dangerous non-communicable disease attacking both women and men and every year it causes thousands of deaths worldwide. Accurate lung nodule segmentation in computed tomography (CT) images can help detect lung cancer early. Since the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5ddf8b8a3efe076895f909de733175e4
https://doi.org/10.3233/faia210154

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AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation

Autor: Md. Mostafa Kamal Sarker, Syeda Furruka Banu, Mohamed Abdel-Nasser, Hatem A. Raswan, Domenec Puig

Publikováno v: Applied Sciences, Vol 11, Iss 10132, p 10132 (2021)
Applied Sciences
Volume 11
Issue 21

Lung cancer is deadly cancer that causes millions of deaths every year around the world. Accurate lung nodule detection and segmentation in computed tomography (CT) images is the most important part of diagnosing lung cancer in the early stage. Most

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::943aae16b813a45170b600b5d681df4b
https://www.mdpi.com/2076-3417/11/21/10132

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Recognizing Food Places in Egocentric Photo-Streams Using Multi-Scale Atrous Convolutional Networks and Self-Attention Mechanism

Autor: Petia Radeva, Farhan Akram, Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Syeda Furruka Banu, Estefania Talavera, Domenec Puig

Publikováno v: IEEE Access, 7, 39069-39082. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
IEEE Access, Vol 7, Pp 39069-39082 (2019)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39dffcade7dd81f8cbeeab975c158995
https://doi.org/10.1109/access.2019.2902225

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Web‐based efficient dual attention networks to detect COVID‐19 from X‐ray images

Autor: Petia Radeva, Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Yasmine Makhlouf, Sylvie Chambon, Domenec Puig

Publikováno v: Electronics Letters
Sarker, M M K, Makhlouf, Y, Banu, S F, Chambon, S, Radeva, P & Puig, D 2020, ' Web-based efficient dual attention networks to detect COVID-19 from X-ray images ', Electronics Letters . https://doi.org/10.1049/el.2020.1962

Rapid and accurate detection of COVID-19 is a crucial step to control the virus For this purpose, the authors designed a web-based COVID-19 detector using efficient dual attention networks, called ‘EDANet’ The EDANet architecture is based on inve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c12805a1cd30697706e2c48d2be2ca89

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SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks

Autor: Vivek Kumar Singh, Hatem A. Rashwan, Forhad U H Chowdhury, Petia Radeva, Domenec Puig, Santiago Romani, Adel Saleh, Md. Mostafa Kamal Sarker, Syeda Furruka Banu, Farhan Akram, Saddam Abdulwahab

Publikováno v: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 ISBN: 9783030009335
MICCAI (2)

Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model represented as an encoder-decoder network. The encoder network is constructed by di

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8ed2199231d730144071205ecbb2c47a
https://doi.org/10.1007/978-3-030-00934-2_3

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