Object Detection
- Developed a TFLite model for the detection of police cars, bikes, and vans.
- Deployed the model in android app
Lung Cancer Detection
- Data Pre-processing: Resized, adjusted the luminance, rescaled, and converted data to uint8
- Training Nodule Detector: A 3D Faster R-CNN Network is used as the detector
- Proposals: The model trained was tested on all data, giving all suspicious nodule locations and confidences
- Training Nodule Classifier: Sampled proposals according to confidence, and for each proposal, cropped cubes, centered at the proposed center
Diabetic Retinopathy Classification
- Developed a deep learning model to classify Diabetic Retinopathy using CNN and transfer learning
- Tech-Stack: Python, Keras
Information-Theoretic Feature Selection from Hyperspectral Images
- Proposed greedy feature selection algorithm using mutual information, Relevancy, Redundancy, and Representability
- Carried out experiments on two hyperspectral images i.e. Indian Pines and Salinas Valley
- A considerable increase in accuracy(5-6 %) as compared to baseline accuracy was observed
- It outperforms existing methods such as mRMR, PCA, and NMIFS even at lower dimensions
- Tech-Stack: Python, Keras
- Publication
