نتائج البحث - "Santiago Romani Also"

المصدر: State of the Art in Neural Networks and their Applications ISBN: 9780128197400
State of the Art in Neural Networks and Their Applications: Volume 1, 153-178
STARTPAGE=153;ENDPAGE=178;TITLE=State of the Art in Neural Networks and Their Applications

مصطلحات موضوعية: Computer science, business.industry, Deep learning, Pattern recognition, CAD, medicine.disease, Convolutional neural network, Breast cancer, SDG 3 - Good Health and Well-being, Computer-aided diagnosis, Region of interest, Feature (computer vision), medicine, Segmentation, Artificial intelligence, business

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dfbdd9db8b58f10055acdb8d8e32c80
https://doi.org/10.1016/B978-0-12-819740-0.00008-5

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9

Academic Journal

An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints.

المؤلفون: Schwarz Schuler, Joao Paulo, Also, Santiago Romani, Puig, Domenec, Rashwan, Hatem, Abdel-Nasser, Mohamed

المصدر: Entropy; Sep2022, Vol. 24 Issue 9, pN.PAG-N.PAG, 15p

مصطلحات موضوعية: ARTIFICIAL neural networks, DIVISIBILITY groups, COLORECTAL cancer, CONVOLUTIONAL neural networks

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10

Breast tumor segmentation in ultrasound images using contextual-information-aware deep adversarial learning framework

المؤلفون: Farhan Akram, Domenec Puig, Vivek Kumar Singh, Santiago Romani, Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Mohamed Abdel-Nasser, Nidhi Pandey

المصدر: Expert Systems with Applications. 162:113870

مصطلحات موضوعية: 0209 industrial biotechnology, Channel (digital image), Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Context (language use), 02 engineering and technology, 020901 industrial engineering & automation, Breast cancer, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, medicine, Segmentation, Breast ultrasound, medicine.diagnostic_test, business.industry, General Engineering, Pattern recognition, Speckle noise, medicine.disease, Computer Science Applications, Weighting, Variable (computer science), ComputingMethodologies_PATTERNRECOGNITION, Metric (mathematics), 020201 artificial intelligence & image processing, Artificial intelligence, business

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::26d96e79146ab97c04277d45dfeaba99
https://doi.org/10.1016/j.eswa.2020.113870

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11

FCA-Net: Adversarial Learning for Skin Lesion Segmentation Based on Multi-Scale Features and Factorized Channel Attention

المؤلفون: Hatem A. Rashwan, Mohamed Abdel-Nasser, Alain Lalande, Vivek Kumar Singh, Nidhi Pandey, Benoit Presles, Farhan Akram, Domenec Puig, Santiago Romani

المساهمون: CRISES Research Group, Universitat Rovira i Virgili, Department of Electrical Engineering, Faculty of Engineering, Aswan University, Faculty of Engineering, Aswan Universit, University of Aswan-University of Aswan, Department of Electrical and Computer Engineering [Abu Dhabi], Khalifa University for Science Technology [Abou Dabi], Bioinformatics Institute [Singapore], Agency for science, technology and research [Singapore] (A*STAR), Imagerie et Vision Artificielle [Dijon] (ImViA), Université de Bourgogne (UB), Spanish GovernmentDPI2016-77415-R

المصدر: IEEE Access
IEEE Access, IEEE, 2019, 7, pp.130552-130565. ⟨10.1109/ACCESS.2019.2940418⟩
IEEE Access, Vol 7, Pp 130552-130565 (2019)

مصطلحات موضوعية: General Computer Science, Computer science, 02 engineering and technology, Residual, Fuzzy logic, 030218 nuclear medicine & medical imaging, Convolution, conditional generative adversarial network, 03 medical and health sciences, Skin lesion, 0302 clinical medicine, Gradient vector flow, 0202 electrical engineering, electronic engineering, information engineering, General Materials Science, Segmentation, [INFO]Computer Science [cs], channel attention, business.industry, residual convolution, General Engineering, Pattern recognition, Kernel (image processing), factorized kernel, 020201 artificial intelligence & image processing, Artificial intelligence, lcsh:Electrical engineering. Electronics. Nuclear engineering, business, Encoder, lcsh:TK1-9971, Dermoscopy images