INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This abstract highlights strides in agriculture through computer vision and machine learning integration, focusing on fruit detection and disease identification. Emphasizing the efficacy of convolutional neural networks (CNNs) and transfer learning for versatile fruit identification, it addresses variations in size and orientation. In disease detection, image processing, and machine learning, employing segmentation, feature extraction, and models like SVMs and deep neural networks ensure precise identification. The paper discusses challenges like dataset diversity, model interpretability, and scalability in real-world implementation. Additionally, it explores edge computing and IoT integration for real-time monitoring in precision agriculture. Overall, these advancements promise efficient crop management.
Keywords:
Computer vision, Machine learning,Convolutional Neural Networks (CNNs),TensorFlow's Keras API
Cite Article:
"Fruite Disease Detection", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d151-d155, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404318.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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