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ConOffense: Multi-modal multitask Contrastive learning for offensive content identification

Hateful or offensive content has been increasingly common on social media platforms in recent years, and the problem is now widespread. …

Debaditya Shome, T. Kar

ConOffense: Multi-modal multitask Contrastive learning for offensive content identification

RestHAR: Residual feature learning transformer for human activity recognition from multi-sensor data

In recent times, surge in the use of smartphones in our daily lives has created a huge opportunity for paving the road towards …

Debaditya Shome

RestHAR: Residual feature learning transformer for human activity recognition from multi-sensor data

FedAffect: Few-Shot Federated Learning for Facial Expression Recognition

Annotation of large-scale facial expression datasets in the real world is a major challenge because of privacy concerns of the …

Debaditya Shome, T. Kar

FedAffect: Few-Shot Federated Learning for Facial Expression Recognition

Sum rate maximization of D2D networks with energy constrained UAVs through deep unsupervised learning

We consider a system model in which several energy harvesting (EH) unmanned aerial vehicles (UAVs), often known as drones, are deployed …

Benjamin Lea, Debaditya Shome, Omer Waqar, Jabed Tomal

Sum rate maximization of D2D networks with energy constrained UAVs through deep unsupervised learning

EmoHinD: Fine-grained multilabel emotion recognition from Hindi texts with Deep learning

Emotion recognition is a critical sub-field within Affective Computing and a step towards comprehensive natural language understanding. …

Debaditya Shome

EmoHinD: Fine-grained multilabel emotion recognition from Hindi texts with Deep learning

Deep Q-learning for 5G network slicing with diverse resource stipulations and dynamic data traffic

5G wireless networks use the network slicing technique that provides a suitable network to a service requirement raised by a network …

Debaditya Shome, Ankit Kudeshia

Deep Q-learning for 5G network slicing with diverse resource stipulations and dynamic data traffic