Implementation of CNN for Plant Leaf Classification

Autor:	Mohammad Diqi, Sri Hasta Mulyani
Rok vydání:	2021
Předmět:	Contextual image classification Computer science business.industry Deep learning Construct (python library) Machine learning computer.software_genre Identification (information) Artificial intelligence Android (operating system) business Leaf classification computer Java Programming Language
Zdroj:	International Journal of Informatics and Computation. 2:1
ISSN:	2714-5263 2685-8711
Popis:	Many deep learning-based approaches for plant leaf stress identification have been proposed in the literature, but there are only a few partial efforts to summarize various contributions. This study aims to build a classification model to enable people or traditional medicine experts to detect medicinal plants by using a scanning camera. This Android-based application implements the Java programming language and labels using the Python programming language to build deep learning applications. The study aims to construct a deep learning model for image classification for plant leaves that can help people determine the types of medicinal plants based on android. This research can help the public recognize five types of medicinal plants, including spinach Duri, Javanese ginseng, Dadap Serep, and Moringa. In this study, the accuracy is 0.86, precision 0.22, f-1 score 0.23, while recall is 0.2375.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5481c2f59db62ed8164b06541807cc9f https://doi.org/10.35842/ijicom.v2i2.28 Zobrazit plný text záznamu