Publications by authors named "Islomjon Shukhratov"
Article Synopsis
- Remote sensing is crucial for tracking forest biodiversity and resources by using various sensors and machine learning methods for data analysis.
- The study focuses on predicting forest characteristics like species, age, height, and basal area to estimate carbon stock using Sentinel-2 satellite data and the XGBoost algorithm, achieving reasonable prediction accuracy.
- Two methods for estimating carbon stock were explored: a direct approach utilizing remote sensing data and a hierarchical approach using inventory characteristics and conversion equations, leading to a comprehensive solution for carbon stock assessment.
Food quality control is an important task in the agricultural domain at the postharvest stage for avoiding food losses. The latest achievements in image processing with deep learning (DL) and computer vision (CV) approaches provide a number of effective tools based on the image colorization and image-to-image translation for plant quality control at the postharvest stage. In this article, we propose the approach based on Generative Adversarial Network (GAN) and Convolutional Neural Network (CNN) techniques to use synthesized and segmented VNIR imaging data for early postharvest decay and fungal zone predictions as well as the quality assessment of stored apples.
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