Developed a deep network using convolutional features for traffic detection and classification. Trained on datasets like PASCAL VOC, Caltech, KITTY, APOLLO, Cityscapes, and self-created datasets.

Trained a network using multimodal features for visually impaired individuals. Fused various features and considered blur effect for training. Used datasets like PASCAL VOC, Caltech, and self-created datasets.

Gaussian process model used for augmented maps. Dataset collected from Dr. Robot. Application for estimating traffic density in indoor environments.

The project us about estimating traffic density in indoor environment. Robot has been used for data set collection

This project is about detection and classification of objects tk help blind people

This is for detection and classification of objects with multimodal features