Abstract:
In Bangladesh huge amount of agricultural products are destroying by the pests every year due to
lack of poor knowledge about pest detection. As we know that manually identification is difficult
for a farmer. So, classic pest detection and identification can ensure excellent productivity. This
would be a fulfil research in the technical area of computer vision. The dataset is typically random
cropping of square size images together with grayscale color and brightness shifts are used here.
Here Convolutional Neural Network (CNN) will be used to do the image recognition and the
algorithm will provide an optimal architecture for image recognition. The big idea behind CNNs
is that a local understanding of an image is good enough. The research contains the proportions of
validation accuracy of 93.46%. This approach resulted in the agriculture sector that will help a
farmer to recognize the insect from harvest. The computer vision and object recognition can be
used with image processing to create an interactive and enlarge user experience of the real world.
This research aims to demonstrate the possibility and test the performance of the project which
only focuses on insect detection in crop plants that recognize the pest which can help a farmer to
get immediate solution of harvest problem.
