首页|Research from Szechenyi Istvan University Provides New Study Findings on Robotic s (Weed Detection and Classification with Computer Vision Using a Limited Image Dataset)
Research from Szechenyi Istvan University Provides New Study Findings on Robotic s (Weed Detection and Classification with Computer Vision Using a Limited Image Dataset)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on robotics are presented i n a new report. According to news reporting originating from Mosonmagyarovar, Hu ngary, by NewsRx correspondents, research stated, "In agriculture, as precision farming increasingly employs robots to monitor crops, the use of weeding and har vesting robots is expanding the need for computer vision." The news correspondents obtained a quote from the research from Szechenyi Istvan University: "Currently, most researchers and companies address these computer v ision tasks with CNN-based deep learning. This technology requires large dataset s of plant and weed images labeled by experts, as well as substantial computatio nal resources. However, traditional feature-based approaches to computer vision can extract meaningful parameters and achieve comparably good classification res ults with only a tenth of the dataset size. This study presents these methods an d seeks to determine the minimum number of training images required to achieve r eliable classification. We tested the classification results with 5, 10, 20, 40, 80, and 160 images per weed type in a four-class classification system. We extr acted shape features, distance transformation features, color histograms, and te xture features."
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