Support Vector Machine Classifier Final Year Projects with Source Code
Support Vector Machine Classifier Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Support Vector Machine Classifier projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.
Support Vector Machine Classifier Final Year Projects
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A Systematic Literature Review on Plant Disease Detection Motivations Classification Techniques Datasets Challenges and Future Trends
This study reviews research on detecting plant pests and diseases using artificial intelligence. The authors analyzed 176 important papers from over 1300 studies to understand how AI, machine learning, and deep learning are used with images and datasets. They found that some methods, like SVMs and cognitive CNNs, perform well, but detecting the exact disease location remains a challenge. The study highlights the need for lightweight models that work on small devices and across many crops. -
Multi-Class Retinal Diseases Detection Using Deep CNN With Minimal Memory Consumption
This project focuses on using machine learning to identify and classify eye diseases. The researchers designed a new neural network model that works efficiently without using too much memory. They tested it on a dataset containing 32 types of retinal diseases. The model performed very well, achieving 95% accuracy while managing resources better than previous methods.
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Support Vector Machine Classifier Project Synopsis & Presentation
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