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Canine Skin Disease Classification Using Convolutional Neural Networks (CNN)

5,500.00
Aim: To develop a custom Convolutional Neural Network (CNN) model for accurately classifying seven common canine skin diseases, thereby improving diagnostic precision and supporting veterinary care.

Real-Time Plant Disease Dataset Development and Detection of Plant Disease Using Deep Learning

5,500.00
Aim: The primary aim of this project is to develop an advanced plant disease detection system that leverages state-of-the-art deep learning architectures, such as ResNet152V2 and EfficientNetV2B3, to achieve higher accuracy, scalability, and efficiency.