Detection of Disease in Bombyx Mori Silkworm by Using Image Analysis Approach

Technology is making remarkable changes in almost every aspects of life. Many branches of agriculture are making use of trending technical invention, yet sericulture is a way behind at implementing these developments. Though many approaches are developed for detection of diseased eggs and moths, detection of diseases in silkworm at an earlier stage is a laborious process. Identification and detection of diseases at an earlier stage would be helpful for a farmer to take essential precaution to avoid spreading of diseases. In this research work image classifying and deep learning model are used to identify the silkworm disease. Using various sets of network layers in deep neural network, a machine has been trained to classify healthy silkworm and unhealthy silkworm which has resulted in promising accuracy rate. Tensorflow platform has been used to create layers and train the machine.