Advancing Ovarian Cancer Diagnosis Through Deep Learning and Explainable AI: A Multiclassification Approach

5,500.00
To develop a robust and interpretable AI system for ovarian cancer diagnosis using multiclassification techniques and advanced deep learning models, including ResNet152V2, EfficientNetV2B3, and ResNet50V2.

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.