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20 results for “Leaf Classification”
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Research ArticleOpen accessPhrase in the titleHarmonic Mean Projection Shape Transform for Leaf ClassificationSophia Jamila Zahra, Riza Sulaiman, Seyed M.M. Kahaki, Anton Satria PrabuwonoShape feature extraction has emerged as an important part of computer vision and image processing applications. Identification of shape objects in huge data based on shape similarity still remains a challenging problem due to the similarity of the shapes and existing of classes with similar contour information. This paper presents to investigate the shape analysis for plant leaf classification by … …Journal of Computer Science, Vol. 16, Issue 9 · 13 Sep 2020 · 6,854 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleExperimental Evaluation of Coffee Leaf Disease Classification and Recognition Based on Machine Learning and Deep Learning AlgorithmsKacoutchy Jean Ayikpa et al.Coffee plant diseases constitute a significant danger to world coffee production, and the greatest challenge is to detect these diseases as early as possible to save the crop. Traditional methods are most often based on visual observations, often with errors in diagnosing diseases. Machine Learning has become a tool that presents itself as an alternative for automatically identifying plant diseases. … …Journal of Computer Science, Vol. 18, Issue 12 · 10 Dec 2022 · 6,986 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Accurate Mango Pest Identification Employing the Gaussian Mixture Model and Expectation-Maximization (EM) AlgorithmD. Lita Pansy, M. MuraliMangoes are fruits that originated in South and Southeast Asia. Mango fruits are consumed in high volume worldwide. However, fruit, stem, root, and mango leaves are damaged by pests, and it has a significant negative impact on mango production. Many works were developed for the pest detection of mango; but, none of the works concentrated on the practical applicability and … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,063 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Hybrid Metaheuristic Algorithm for Diseases Classification Using UAV ImagesYagnasree Sirivella, Anuj JainRecent advances in technology are very astounding since they have made it possible to manage and monitor systems remotely. Traditional farming is undergoing a transition towards "smart farming" with the assistance of technological breakthroughs, which include the implementation of intelligent irrigation systems and the remote monitoring of the development of crops. In particular, the Unmanned Aerial Vehicle plays a significant … …Journal of Computer Science, Vol. 19, Issue 10 · 11 Sep 2023 · 5,251 accessesView PDFCite
Research ArticleOpen accessIn the keywordsLEAF FEATURES EXTRACTION AND RECOGNITION APPROACHES TO CLASSIFY PLANTMohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib, Illiasaak AhmadPlant classification based on leaf identification is becoming a popular trend. Each leaf carries substantial information that can be used to identify and classify the origin or the type of plant. In medical perspective, images have been used by doctors to diagnose diseases and this method has been proven reliable for years. Using the same method as doctors, researchers try … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 7,362 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 535 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhenetic Analysis of Polypodiaceae Ferns in Nagarawangi Village, Sumedang District, IndonesiaSuryana, Asep Zaenal Mutaqien, Joko Kusmoro et al.Polypodiaceae is a family of ferns with the largest members and a wide distribution in forest and high-humidity areas. The availability suggests the need for Phenetic analysis of Polypodiaceae in Nagarawagi Village to facilitate the classification of ferns as well as create a database of flora and fauna diversity in Indonesia. Therefore, this study aimed to determine the species and … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 7 Aug 2026 · 889 accessesView PDFCite