Muhammad Shahid

Orcid: 0000-0002-4573-0379

Affiliations:
  • University of Genoa, Italy (PhD 2021)


According to our database1, Muhammad Shahid authored at least 12 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

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Bibliography

2025
Cost-Efficient and Portable IoMT Solution for Post-Stroke Rehabilitation: Inferring Feet Pressures With Lower Limbs IMUs.
IEEE Internet Things J., May, 2025

2024
Replacing Force Plates with IMU-Based SmartGlasses for Balance Assessment.
Proceedings of the IEEE International Conference on E-health Networking, 2024

2023
Feet Pressure Prediction from Lower Limbs IMU Sensors for Wearable Systems in Remote Monitoring Architectures.
Proceedings of the IEEE Global Communications Conference, 2023

2021
Social Interactions Analysis through Deep Visual Nonverbal Features.
PhD thesis, 2021

RealVAD: A Real-World Dataset and A Method for Voice Activity Detection by Body Motion Analysis.
IEEE Trans. Multim., 2021

Personality Traits Classification Using Deep Visual Activity-Based Nonverbal Features of Key-Dynamic Images.
IEEE Trans. Affect. Comput., 2021

S-VVAD: Visual Voice Activity Detection by Motion Segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020
RealVAD: A Real-world Dataset for Voice Activity Detection.
Dataset, July, 2020

Analysis of Face-Touching Behavior in Large Scale Social Interaction Dataset.
Proceedings of the ICMI '20: International Conference on Multimodal Interaction, 2020

2019
Comparisons of Visual Activity Primitives for Voice Activity Detection.
Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019

Voice Activity Detection by Upper Body Motion Analysis and Unsupervised Domain Adaptation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Investigation of Small Group Social Interactions Using Deep Visual Activity-Based Nonverbal Features.
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018


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