Mohd Hanief Wani

• Guided MCA final-semester students in the implementation of projects.
• Research Outcome:

1. Deep Learning-Based Video Surveillance System for Suspicious Activity Detection(SCI-Accepted)

2. EASAD: Efficient and Accurate Suspicious Activity Detection Using Deep-Learning Model for IoT-Based Video Surveillance(Scopus-Accepted)

3. Sophisticated face mask dataset: a novel dataset for effective coronavirus disease surveillance(Scopus-Published)

4. Deep Ensemble Model with Improved Score level fusion for Suspicious Activity Detection(SCI-under review)

5. Suspicious Action Recognition Model via Improved Deep Joint Segmentation and Hybrid Model

(SCI-under review)

6. 4 scopus conference papers