Advanced detection of fungi-bacterial diseases in plants using modified deep neural network and DSURF

Abstract Food is indispensable for humans as their growth and survival depend on it. But nowadays, crop getting spoiled due to fungi bacteria soil temperature are changes very rapidly according sudden climate changes. Due fungi-bacterial crop, the quality of food declining day by this really not good human health. The goal research paper advanced detection diseases in plants using modified deep neural network approach DSURF method order enhance process. Proposed use artificial intelligence techniques like model dynamic SURF identify classify plant fungus bacteria. Additionally, support feature extraction & classifier combinations creating image clusters with help Clustering. Deep learning employed training testing classifier. quantitative experimental results work claimed that authors have achieved 99.5% overall accuracy implementing DNNM which much higher than other previous proposed methods field. This a step towards finding best practices detect from any bacterial fungal infection so can get healthy food.