Title: Classification of fungal diseases in plant based on deep learning techniques

Abstract

India has a wide range of agricultural and ecological varieties. India is the leading producer of milk, pulses, jute, rice, wheat, sugarcane, vegetables, fruits, and cotton. The average yield of many Indian crops is inferior. Plant diseases are one of the significant causes of the low yield of crops. These diseases are caused by micro-organisms such as bacteria, viruses and fungi. This article reveals the research findings of the classification of fungi-affected diseases of popular fruit plants such as Apple, Custard Apple and Guava based on their camera-captured (14,412 images) and microscopic images (602 images). Besides, it calculates the infected area of the leaf for further processing. The experimental results are exciting and highly encouraging to justify as state-of-the-art results, i.e. 97.52%.

Biography

Mallikarjun Hangarge, Associate Professor and Head Department of P. G. Studies and Research in Computer Science, Karnatak Arts, Science and Commerce College, Bidar. He received a prestigious IAPR Travel grant to attend ICPR in Hongkong in 2006. UGC Travel grants to present his research at ICDAR, 2013 at Washington DC USA, in 2013. He has received three Best Paper Awards at International conferences. He received Faculty Summer Research Fellowship in 2012 from the Indian Academy of Sciences. He has completed three major research projects of Rs. 30.0 lakhs. He has collaborated with the University of South Dakota, USA, Computer Vision and Pattern Recognition Unit, Indian Statistical Institute Kolkata and Speech Processing Laboratory, IIIT Hyderabad. His research interests are in Image Processing and Pattern Recognition and its applications such as Automatic Handwriting Analysis, Document Image Processing, etc. He is the author of more than 100 research articles and three books published in reputed International and National Journals and conferences. He serves on the Editorial Board of 6 International Journals.