1.
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14 p, 1.3 MB |
Image-based Mangifera Indica Leaf Disease Detection using Transfer Learning for Deep Learning Methods
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Dhawan, Kshitij (Vellore Institute of Technology School of Information Technology and Engineering (Índia)) ;
Ramalingam, Srinivasa Perumal (Vellore Institute of Technology School of Information Technology and Engineering (Índia)) ;
Ramu Krishnansh, Nadesh (Vellore Institute of Technology School of Information Technology and Engineering (Índia))
Mangifera Indica, ordinarily known as mango, comes from a large tree. The leaf of the mango tree has human health benefits; the mango leaf extract is used for curing various diseases, including patients with cancer and diabetes. [...] Mangifera Indica, ordinarily known as mango, comes from a large tree. The leaf of the mango treehas human health benefits; the mango leaf extract is used for curing various diseases, including patientswith cancer and diabetes. [...]
2023 - 10.5565/rev/elcvia.1660
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 22 Núm. 2 (2023) , p. 27-40 (Regular Issue)
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2.
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15 p, 2.9 MB |
Adopting transfer learning for neuroimaging : a comparative analysis with a custom 3D convolution neural network model
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Soliman, Amira (Halmstad University) ;
Chang, Jose R. (National Cheng Kung University in Tainan) ;
Etminani, Kobra (Halmstad University) ;
Byttner, Stefan (Halmstad University) ;
Davidsson, Anette (Institution of Medicine and Health Sciences) ;
Martínez-Sanchis, Begoña (Hospital Universitari i Politècnic La Fe (València)) ;
Camacho, Valle (Hospital de la Santa Creu i Sant Pau (Barcelona, Catalunya)) ;
Bauckneht, Matteo (IRCCS Ospedale Policlinico San Martino) ;
Stegeran, Roxana (Linköping University Hospital) ;
Ressner, Marcus (Linköping University Hospital) ;
Agudelo-Cifuentes, Marc (Hospital Universitari i Politècnic La Fe (València)) ;
Chincarini, Andrea (National Institute of Nuclear Physics) ;
Brendel, Matthias (University Hospital) ;
Rominger, Axel (University Hospital Bern) ;
Bruffaerts, Rose (University of Antwerp) ;
Vandenberghe, Rik (University Hospitals Leuven (Bèlgica)) ;
Kramberger, Milica G. (University Medical Centre) ;
Trost, Maja (University of Ljubljana) ;
Nicastro, Nicolas (Geneva University Hospitals (Suïssa)) ;
Frisoni, Giovanni B. (University Hospitals) ;
Lemstra, Afina W. (VU Medical Center Alzheimer Center) ;
Berckel, Bart N. M. van (Vrije Universiteit Amsterdam) ;
Pilotto, Andrea (University of Brescia) ;
Padovani, Alessandro (IRCCS Ospedale Policlinico San Martino) ;
Morbelli, Silvia (Stavanger University Hospital) ;
Aarsland, Dag (King's College London) ;
Nobili, Flavio (University of Genoa) ;
Garibotto, Valentina (Geneva University) ;
Ochoa-Figueroa, Miguel (Linköping University) ;
Universitat Autònoma de Barcelona
In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. [...]
2022 - 10.1186/s12911-022-02054-7
BMC Medical Informatics and Decision Making, Vol. 22 (december 2022)
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3.
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14 p, 3.9 MB |
Beyond eleven color names for image understanding
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Yu, Lu (Centre de Visió per Computador (Bellaterra, Catalunya)) ;
Zhang, Lichao (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ;
Weijer, Joost van de (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ;
Khan, Fahad Shahbaz (Linköping University. Computer Vision Laboratory) ;
Cheng, Yongmei (Northwestern Polytechnical University. Key Laboratory of Information Fusion Technology (China)) ;
Parraga, Carlos Alejandro (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Color description is one of the fundamental problems of image understanding. One of the popular ways to represent colors is by means of color names. Most existing work on color names focuses on only the eleven basic color terms of the English language. [...]
2018 - 10.1007/s00138-017-0902-y
Machine Vision and Applications, Vol. 29, Issue 2 (February 2018) , p. 361-373
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4.
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36 p, 19.5 MB |
A framework of filtering rules over ground truth samples to achieve higher accuracy in land cover maps
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Padial-Iglesias, Mario (Universitat Autònoma de Barcelona. Departament de Geografia) ;
Serra Ruiz, Pere (Universitat Autònoma de Barcelona. Departament de Geografia) ;
Ninyerola i Casals, Miquel (Universitat Autònoma de Barcelona. Departament de Biologia Animal, de Biologia Vegetal i d'Ecologia) ;
Pons, Xavier (Universitat Autònoma de Barcelona. Departament de Geografia)
Remote Sensing (RS) digital classification techniques require sufficient, accurate and ubiquitously distributed ground truth (GT) samples. GT is usually considered "true" per se; however, human errors, or differences in criteria when defining classes, among other reasons, often undermine this veracity. [...]
2021 - 10.3390/rs13142662
Remote sensing (Basel), Vol. 13, Issue 14 (July 2021) , art. 2662
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5.
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16 p, 4.4 MB |
Oil palm (Elaeis guineensis) mapping with details : smallholder versus industrial plantations and their extent in riau, Sumatra
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Descals, Adrià (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Szantoi, Zoltan (Stellenbosch University) ;
Meijaard, Erik (Borneo Future) ;
Sutikno, Harsono (Austindo Nusantara Jaya Tbk) ;
Rindanata, Guruh (Austindo Nusantara Jaya Tbk) ;
Wich, Serge (Liverpool John Moores University. School of Biological and Environmental Sciences)
Oil palm is rapidly expanding in Southeast Asia and represents one of the major drivers of deforestation in the region. This includes both industrial-scale and smallholder plantations, the management of which entails specific challenges, with either operational scale having its own particular social and environmental challenges. [...]
2019 - 10.3390/rs11212590
Remote sensing (Basel), Vol. 11, issue 21 (Nov. 2019) , art. 2590
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10.
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17 p, 1.4 MB |
An Evaluation of Perceptual Classification led by Cognitive Models in Traffic Scenes
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Mansouri, Fatimaezzahra (Computer Systems Engineering Laboratory (Marràqueix, Marroc). Department of computer science) ;
Sadgal, Mohamed (Computer Systems Engineering Laboratory (Marràqueix, Marroc). Department of computer science) ;
Elfazziki, Abdelaziz (Computer Systems Engineering Laboratory (Marràqueix, Marroc). Department of computer science) ;
Benchikhi, Loubna (Computer Systems Engineering Laboratory (Marràqueix, Marroc). Department of computer science)
The objects extraction and recognition constitute the most important link in the image processing and understanding, and it cannot be achieved without a solid objects organization during the processing through the learning mechanisms. [...]
2015 - 10.5565/rev/elcvia.699
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 14 núm. 1 (2015) , p. 38-60 (Regular Issue)
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