Person Name
Research on "People" in the context of AI focuses on understanding and improving human-AI interaction across various domains. Current efforts center on enhancing AI's ability to accurately perceive and respond to human nuances, including emotional states, communication styles, and diverse physical characteristics, often employing large language models (LLMs), generative adversarial networks (GANs), and attention networks. This research is crucial for developing more inclusive and effective AI systems, improving accessibility for individuals with disabilities, and mitigating potential biases in AI applications.
Papers
A cost effective eye movement tracker based wheel chair control algorithm for people with paraplegia
Skanda Upadhyaya, Shravan Bhat, Siddhanth P. Rao, V Ashwin, Krishnan Chemmangat
OIMNet++: Prototypical Normalization and Localization-aware Learning for Person Search
Sanghoon Lee, Youngmin Oh, Donghyeon Baek, Junghyup Lee, Bumsub Ham
AI-Based Automated Speech Therapy Tools for persons with Speech Sound Disorders: A Systematic Literature Review
Chinmoy Deka, Abhishek Shrivastava, Ajish K. Abraham, Saurabh Nautiyal, Praveen Chauhan
Using consumer feedback from location-based services in PoI recommender systems for people with autism
Noemi Mauro, Liliana Ardissono, Stefano Cocomazzi, Federica Cena