2026-06-16
14:12 |
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16 p, 1.9 MB |
Implementation of CNN Voting based Technique for Classification of Lung Images
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Tanga, Champa (Rajiv Gandhi University, Doimukh, Arunachal Pradesh, India) ;
Roy, Amarjit (Ghani Khan Choudhury Institute of Engineering and Technology, Malda, West Bengal, India) ;
Rahul, Jagdeep (Rajiv Gandhi University, Doimukh, Arunachal Pradesh, India) ;
Islam, Mohiul (Vellore Institute of Technology, Vellore, Tamil Nadu, India) ;
Sain, Chiranjit (Ghani Khan Choudhury Institute of Engineering and Technology, Malda, West Bengal, India) ;
Ustun, Taha Selim (Fukushima Renewable Energy Institute, Koriyama, Japan)
Lung-related disorders such as pneumonia, cancer, and tuberculosis remain significant health concerns in recent decades. This research proposes a voting-based ensemble of pretrained CNN models to accurately classify lung disorders, such as pneumonia, tuberculosis, and COVID-19, from medical images. [...]
2026 -  10.5565/rev/elcvia.2366
ELCVIA, Vol. 25, Num. 2 (2026) , p. 38-54 (Regular Issue)
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2026-06-16
13:12 |
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19 p, 614.3 KB |
Arabic Sign Language Recognition with Deep Learning Models and Keypoint Landmarks
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Alshanik, Farah (Jordan University of Science and Technology) ;
Aljunidi, Saif (Yarmouk University, Irbid, Jordan) ;
Qawasmeh, Ethar (Yarmouk University, Irbid, Jordan)
Communication is a fundamental aspect of human interaction, essential for expressing emotions and building relationships. While individuals with typical hearing rely on spoken language, the deaf and mute community communicates through visual gestures and facial expressions, commonly known as sign language. [...]
2026 - 10.5565/rev/elcvia.2317
ELCVIA, Vol. 25, Num. 2 (2026) , p. 1-19 (Regular Issue)
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2026-06-16
10:13 |
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14 p, 4.9 MB |
Using Hybrid Pre-trained Convolutional Neural Networks and SVM Based VGG16, ResNet50, and DeseNet201 for Identifying Plant Leaf Disease
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Yaareb, Sura (Higher Education and Scientific Research, Baghdad, Iraq) ;
Daami, Rajaa (University of Information Technology and Communications, Baghdad, Iraq) ;
Muayad, Hasan (University of Information Technology and Communications, Baghdad, Iraq) ;
Nafea, Ali (University of Information Technology and Communications, Baghdad, Iraq) ;
AL-DULAIMI, Khamael (Al-Nahrain University-Collage of Science- Computer Science, Baghdad, Iraq)
Purpose: Early and accurate detection of plant leaf diseases is vital for safe- guarding crop yield and supporting sustainable agricultural practices. However, practical deployment faces challenges such as inconsistent lighting conditions, overlapping leaves, low-contrast early-stage symptoms, and noisy image data-all of which hinder the reliability of deep learning models in field environments. [...]
Purpose: Early and accurate detection of plant leaf diseases is vital for safe-guarding crop yield and supporting sustainable agricultural practices. However,practical deployment faces challenges such as inconsistent lighting conditions,overlapping leaves, low-contrast early-stage symptoms, and noisy image data-allof which hinder the reliability of deep learning models in field environments. [...]
2026 - 10.5565/rev/elcvia.2198
ELCVIA, Vol. 25, Num. 2 (2026) , p. 55-68 (Regular Issue)
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2026-06-16
13:12 |
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18 p, 3.6 MB |
Classification of Banana Leaf Disease Using Random Forest Based on LAB Color Features and Segmentation Area
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Makmur, Haerunnisya (State University of Makassar, Makassar, Indonesia) ;
Nasrullah, Asmaul Husna (State University of Makassar, Makassar, Indonesia) ;
Budiarti, Nur Azizah Eka (State University of Makassar, Makassar, Indonesia) ;
Zain, Satria Gunawan (State University of Makassar, Makassar, Indonesia) ;
Wahid, Abdul (State University of Makassar, Makassar, Indonesia)
Banana (Musa spp. ) is an important commodity in tropical and subtropical countries, serving as a major source of income for farmers and a staple food for millions of people worldwide. As such, banana has a high export value, prompting increased production to meet the growing market demand. [...]
2026 - 10.5565/rev/elcvia.1989
ELCVIA, Vol. 25, Num. 2 (2026) , p. 20-38 (Regular Issue)
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2026-04-27
09:42 |
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27 p, 4.9 MB |
Optimizing Predicate Detection : a novel approach using ResNet152 architecture and NAdam optimizer
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Ouazzani Chahdi, Meryem (Sidi Mohamed Ben Abdellah University (Marroc)) ;
Ouazzani Chahdi, Adnane (Sidi Mohamed Ben Abdellah University (Marroc)) ;
Annich, Afafe (Sidi Mohamed Ben Abdellah University (Marroc)) ;
Satori, Khalid (Sidi Mohamed Ben Abdellah University (Marroc)) ;
El Abderrahmani, Abdellatif (Sidi Mohamed Ben Abdellah University (Marroc))
Visual relationship detection is crucial for semantic scene compre-hension, impacting various fields, including Human Behavior Analysis, Visual Navigation, Medicine, and Security. A key challenge in this domain is manag-ing partially visible objects and occluded object, which complicate the accurate detection of triplet relationships. [...]
2026 - 10.5565/rev/elcvia.2131
ELCVIA, Vol. 25, Num. 1 (2026) , p. 98-123 (Regular Issue)
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2026-04-10
15:12 |
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2026-04-10
17:12 |
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2026-04-10
17:12 |
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2026-04-10
18:12 |
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21 p, 6.0 MB |
Enhanced underwater fish image processing by noise elimination, saturation adjustment, and edge sharpening technique
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Khan, Samra Urooj (University Malaysia Pahang Al-Sultan Abdullah (Malàisia)) ;
Faisal, Sundas (Silesian University of Technology) ;
Ghazali, Kamarul Hawari (University Malaysia Pahang Al-Sultan Abdullah (Malàisia))
Analyzing underwater images and improving their quality is a difficult task for researchers. Processing underwater images is extremely difficult because of the low contrast, noise, and blurriness brought on by light scattering and absorption. [...]
2026 - 10.5565/rev/elcvia.2285
ELCVIA, Vol. 25, Num. 1 (2026) , p. 42-62 (Regular Issue)
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2026-04-10
18:12 |
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