Agriculture technology is pursuing the field of artificial intelligence to enhance its productions. The major concern is accurate disease identification and making its possible solution with even 99.9% accuracy. Deep learning technique is one of the best technologies to solve this problem. Mask region-based convolutional neural network (Mask R-CNN) is the best feet for image segmentation or more specific disease area identification of paddy crops. Image processing is playing an important role in disease feature extraction. In this paper, we will discuss image segmentation using Mask R-CNN technique and disease image feature pre-preprocessing along with edge, counter, area, image enhancement, high, width, multiple correlations, and color space analysis. We used a digital image processing technique for feature extraction. The programming results prove the revolution of new cutting edge enhancement in the agricultural field.
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