Zobrazeno 1 - 10
of 488
pro vyhledávání: '"Bhargava Bharat"'
Autor:
Palash, Mijanur, Bhargava, Bharat
In this paper, we present SAFER, a novel system for emotion recognition from facial expressions. It employs state-of-the-art deep learning techniques to extract various features from facial images and incorporates contextual information, such as back
Externí odkaz:
http://arxiv.org/abs/2306.09372
Autor:
Palash, Mijanur, Bhargava, Bharat
Publikováno v:
AAAI Spring Symposium 2022
Current works in human emotion recognition follow the traditional closed learning approach governed by rigid rules without any consideration of novelty. Classification models are trained on some collected datasets and expected to have the same data d
Externí odkaz:
http://arxiv.org/abs/2306.08733
Autor:
Palash, Mijanur, Bhargava, Bharat
Automatic emotion recognition has recently gained significant attention due to the growing popularity of deep learning algorithms. One of the primary challenges in emotion recognition is effectively utilizing the various cues (modalities) available i
Externí odkaz:
http://arxiv.org/abs/2306.08657
Autor:
Palacios, Servio, Ault, Aaron, Krogmeier, James V., Bhargava, Bharat, Brinton, Christopher G.
This paper introduces AGAPECert, an Auditable, Generalized, Automated, Privacy-Enabling, Certification framework capable of performing auditable computation on private data and reporting real-time aggregate certification status without disclosing und
Externí odkaz:
http://arxiv.org/abs/2207.12482
The smart features of modern cars are enabled by a number of Electronic Control Units (ECUs) components that communicate through an in-vehicle network, known as Controller Area Network (CAN) bus. The fundamental challenge is the security of the commu
Externí odkaz:
http://arxiv.org/abs/2104.03763
This paper introduces an adaptive model-free deep reinforcement approach that can recognize and adapt to the diurnal patterns in the ride-sharing environment with car-pooling. Deep Reinforcement Learning (RL) suffers from catastrophic forgetting due
Externí odkaz:
http://arxiv.org/abs/2104.00203
Autor:
Bonjour, Trevor, Haliem, Marina, Alsalem, Aala, Thomas, Shilpa, Li, Hongyu, Aggarwal, Vaneet, Kejriwal, Mayank, Bhargava, Bharat
Learning to adapt and make real-time informed decisions in a dynamic and complex environment is a challenging problem. Monopoly is a popular strategic board game that requires players to make multiple decisions during the game. Decision-making in Mon
Externí odkaz:
http://arxiv.org/abs/2103.00683
The ubiquitous growth of mobility-on-demand services for passenger and goods delivery has brought various challenges and opportunities within the realm of transportation systems. As a result, intelligent transportation systems are being developed to
Externí odkaz:
http://arxiv.org/abs/2011.08999
Significant development of ride-sharing services presents a plethora of opportunities to transform urban mobility by providing personalized and convenient transportation while ensuring efficiency of large-scale ride pooling. However, a core problem f
Externí odkaz:
http://arxiv.org/abs/2010.01755