SVM
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 Read article
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Facial Recognition in Education: Revolutionizing Attendance Tracking for Enhanced Efficiency and Security
Abstract: The goal of this project is to develop a facial recognition-based attendance system for educational institutions to improve and modernize the current system and make it more effective and efficient than it was in the past. The distinctive features of the human face allow for individual identification. Since there is little chance of a face deviating or being duplicated, it is utilized to trace identification. The article also covers the …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Estimation of Crop Yield Prediction Using Machine Learning Technique.
Abstract: Agriculture serves as the primary source of livelihood for a significant portion of India's population, but it faces a myriad of challenges, including climate variability, soil fertility issues, and reliance on traditional farming practices. To address these challenges, researchers are increasingly turning to machine learning (ML) methodologies to predict crop yields more accurately. Studies have delved into the effectiveness of various ML algorithms such as Random Forest, Gaussian Process Regression, …
Published in International Journal of Agrochemistry · Vol. 10, Issue 1, 2024 · pp. 7–12 Read article