A PLANT RECOGNITION APPROACH USING HIGH RESOLUTION NETWORK

Abstract

Plant species recognition plays an important role in agriculture, the pharmaceutical industry, and conservation. The traditional approaches may take days and have difficulties for non-experts. Several computer vision-based models have been proposed, which can partially assist and speed up the plant recognition process. Thanks to the development of data collection and computational systems, the models based on machine learning have considerably improved their performance in the last decades. In this paper, we present a model for plant recognition in Southeast Asia based on the high-resolution network. The evaluation is carried out on a public dataset consisting of 26 different species in Southeast Asia. It shows high accuracy in recognition.