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ORCIDVarsha Suresh
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2020 – today
- 2024
[j1]Farrukh Pervez
, Moazzam Shoukat, Varsha Suresh, Muhammad Umar Bin Farooq, Moid Sandhu, Adnan Qayyum, Muhammad Usama, Anna M. Girardi, Siddique Latif, Junaid Qadir:
Medicine's New Rhythm: Harnessing Acoustic Sensing via the Internet of Audio Things for Healthcare. IEEE Open J. Comput. Soc. 5: 491-510 (2024)- [c6]Varsha Suresh, Salah Aït-Mokhtar, Caroline Brun, Ioan Calapodescu:
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks. ICASSP 2024: 10676-10680 - [i5]Varsha Suresh, Salah Aït-Mokhtar, Caroline Brun, Ioan Calapodescu:
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks. CoRR abs/2406.14747 (2024) - 2023
- [i4]Varsha Suresh, Desmond C. Ong:
Using Positive Matching Contrastive Loss with Facial Action Units to mitigate bias in Facial Expression Recognition. CoRR abs/2303.04896 (2023) - 2022
- [c5]Varsha Suresh:
Context-Dependent Deep Learning for Affective Computing. ACIIW 2022: 1-5 - [c4]Varsha Suresh, Desmond C. Ong:
Using Positive Matching Contrastive Loss with Facial Action Units to mitigate bias in Facial Expression Recognition. ACII 2022: 1-8 - [c3]Yuang Shi, Varsha Suresh, Wei Tsang Ooi:
Shape-Based Conditional Neural Field for Wrist-Worn Change-Point Detection. PerCom Workshops 2022: 787-792 - 2021
- [c2]Varsha Suresh, Desmond C. Ong:
Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition. ACII 2021: 1-8 - [c1]Varsha Suresh, Desmond C. Ong:
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification. EMNLP (1) 2021: 4381-4394 - [i3]Yan San Kong, Varsha Suresh, Jonathan Soh, Desmond C. Ong:
A Systematic Evaluation of Domain Adaptation in Facial Expression Recognition. CoRR abs/2106.15453 (2021) - [i2]Varsha Suresh, Desmond C. Ong:
Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition. CoRR abs/2108.00194 (2021) - [i1]Varsha Suresh, Desmond C. Ong:
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification. CoRR abs/2109.05427 (2021)
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