Embedded Files
Module 1: Image Processing with OpenCV Python: A Practical Introduction
Basic Image Manipulation
Image Enhancement
Color Spaces
Image Filtering and Edge Detection
Morphological Transformations
Image Transforms
Image Segmentation etc.
Module 2: Deep Learning Fundamentals
Neural networks and CNN architectures
Training and optimizing deep learning models
Hands-on projects with TensorFlow with Keras/ PyTorch.
Models Fine-tuning on custom datasets for specific research tasks.
Module 3: Explainable AI for Deep Learning Models
Visualizing Model Predictions and Understanding Feature Importance
Generating Explanations for Image Classification and Object Detection
Case Studies: Applying XAI to Real-world Problems.
Module 4: Research Writing and Dissemination
Structuring and Drafting Impactful Research Papers
Literature Review, Critical Analysis and Finding Research Gaps
Formulating Research Questions and Hypotheses
Designing Experiments and Collecting Data
Writing (Using Overleaf- Latex) and Publishing Research Papers
Preparing figures, tables, and supplementary materials.
Peer Review Process and Responding to Reviewer Comments.
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