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Original Research | Computer Science and Engineering | Volume 15 Issue 5, May 2026 | Pages: 1747 - 1750 | India
Review of Identification of Medicinal and Cosmetic Plants Using Deep Learning
Abstract: Medicinal and Cosmetic plants identification plays a vital role in preserving traditional healthcare systems and ensuring safe therapeutic usage. With increasing loss of botanical expertise and rapid environmental changes, automated identification systems have become essential. This review analyzes the application of deep learning techniques for Medicinal and Cosmetic plants recognition. It examines traditional identification approaches, digital systems, convolutional neural network architectures, transfer learning strategies, performance benchmarks, and deployment considerations. The analysis highlights that lightweight architectures such as MobileNetV2 achieve 85-90% accuracy while remaining suitable for mobile and field deployment. The study also emphasizes the importance of integrating medicinal databases, safety information, and confidence scoring mechanisms for practical use. Finally, the paper identifies research gaps and outlines future directions, including multi-organ recognition, region-specific datasets, and offline-capable mobile applications.
Keywords: Medicinal and Cosmetic plants identification, Deep learning, CNN, Transfer learning, MobileNetV2, AI in agriculture, Traditional medicine
How to Cite?: Snehal H. Pimple, Dr. Ashwini S. Gaikwad, "Review of Identification of Medicinal and Cosmetic Plants Using Deep Learning", Volume 15 Issue 5, May 2026, International Journal of Science and Research (IJSR), Pages: 1747-1750, https://www.ijsr.net/getabstract.php?paperid=SR26522215154, DOI: https://dx.dx.doi.org/10.21275/SR26522215154