Abstract
The pharmaceutical industry is paying more attention to medicinal plants since they are less likely to cause undesirable responses and are less expensive than current medicines. These features have attracted researchers interest in automatic medicinal plant recognition. There are several ways to improve the powerful medicinal plant classifier that can be useful in real-time classification. This work uses several reliable and effective deep-learning techniques for classifying plants based on leaf images. The recent research work is collected systematically and categorized based on their techniques. Further, the dataset details, performance measures used for evaluation, tools utilized for implementation, and chronological review of the collected works are discussed. Finally, this research is concluded with an analysis of eminent ongoing opportunities and research perspectives for improvement in this domain.
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Diwedi, H.K., Misra, A., Tiwari, A.K., Mahmood, A. (2023). Research Review and Literature Perception Towards Medicinal Plants Classification Using Deep Learning Techniques. In: Borah, S., Gandhi, T.K., Piuri, V. (eds) Advanced Computational and Communication Paradigms . ICACCP 2023. Lecture Notes in Networks and Systems, vol 535. Springer, Singapore. https://doi.org/10.1007/978-981-99-4284-8_21
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