Published December 10, 2023
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A Convolutional Neural Network For Classification Cotton Boll Opening Degree
- 1. Doctor of Technical Sciences, Department of Information Processing and Management, Professor Tashkent State Technical University named after Islam Karimov
- 2. Doctoral Candidate, Department of Information Processing and Management Tashkent State Technical University named after Islam Karimov
- 3. PhD, Department of Information Processing and Management, Associate professor Tashkent State Technical University named after Islam Karimov
Description
The paper is devoted to the development of a cotton boll opening degree classification algorithm based on a convolutional neural network. A neural network consisting of convolutional layers, subsampling layers, and full-link layers was used in the study. The aim of the work is to classify cotton boll samples according to their opening degree. The classification criteria are minimizing the number of errors and achieving high accuracy. In the process of creating the algorithm, the data obtained by computing and image processing software were used. In this paper, a number of experiments were conducted with different parameters of convolutional neural networks and training samples to optimize the classification process. The final algorithm was tested on real cotton samples and demonstrated high classification accuracy.
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