484 citations · 590 across the 15 of their papers we have counts for
18 papers
VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings
Vivek Kumar, Sushmita Singh, Prayag Tiwari
Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emotion Classification from essays written in reaction to news articles. Emotion detection from complex dialogue…
An Explainable Model-Agnostic Algorithm for CNN-based Biometrics Verification
Fernando Alonso-Fernandez, Kevin Hernandez-Diaz, Jose M. Buades +2
This paper describes an adaptation of the Local Interpretable Model-Agnostic Explanations (LIME) AI method to operate under a biometric verification setting. LIME was initially pro…
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting
Guojun Liang, Prayag Tiwari, Sławomir Nowaczyk +2
Graph neural networks (GNNs), especially dynamic GNNs, have become a research hotspot in spatio-temporal forecasting problems. While many dynamic graph construction methods have be…
A Novel Deep Learning based Model for Erythrocytes Classification and Quantification in Sickle Cell Disease
Manish Bhatia, Balram Meena, Vipin Kumar Rathi +5
The shape of erythrocytes or red blood cells is altered in several pathological conditions. Therefore, identifying and quantifying different erythrocyte shapes can help diagnose va…
Huatuo-26M, a Large-scale Chinese Medical QA Dataset
Jianquan Li, Xidong Wang, Xiangbo Wu +6
In this paper, we release a largest ever medical Question Answering (QA) dataset with 26 million QA pairs. We benchmark many existing approaches in our dataset in terms of both ret…
A Survey on Few-Shot Class-Incremental Learning
Songsong Tian, Lusi Li, Weijun Li +3
Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for dee…
An Overview of Violence Detection Techniques: Current Challenges and Future Directions
Nadia Mumtaz, Naveed Ejaz, Shabana Habib +4
The Big Video Data generated in today's smart cities has raised concerns from its purposeful usage perspective, where surveillance cameras, among many others are the most prominent…
Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk
Benyou Wang, Xiangbo Wu, Xiaokang Liu +3
Language is the principal tool for human communication, in which humor is one of the most attractive parts. Producing natural language like humans using computers, a.k.a, Natural L…
EEG based Emotion Recognition: A Tutorial and Review
Xiang Li, Yazhou Zhang, Prayag Tiwari +6
Emotion recognition technology through analyzing the EEG signal is currently an essential concept in Artificial Intelligence and holds great potential in emotional health care, hum…
MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare
Shaoxiong Ji, Tianlin Zhang, Luna Ansari +3
Mental health is a critical issue in modern society, and mental disorders could sometimes turn to suicidal ideation without adequate treatment. Early detection of mental disorders…
Pre-trained Language Models in Biomedical Domain: A Systematic Survey
Benyou Wang, Qianqian Xie, Jiahuan Pei +4
Pre-trained language models (PLMs) have been the de facto paradigm for most natural language processing (NLP) tasks. This also benefits biomedical domain: researchers from informat…
Deep Learning for Depression Recognition with Audiovisual Cues: A Review
Lang He, Mingyue Niu, Prayag Tiwari +9
With the acceleration of the pace of work and life, people have to face more and more pressure, which increases the possibility of suffering from depression. However, many patients…
Structural block driven - enhanced convolutional neural representation for relation extraction
Dongsheng Wang, Prayag Tiwari, Sahil Garg +2
In this paper, we propose a novel lightweight relation extraction approach of structural block driven - convolutional neural learning. Specifically, we detect the essential sequent…
Kernel Method based on Non-Linear Coherent State
Prayag Tiwari, Shahram Dehdashti, Abdul Karim Obeid +2
In this paper, by mapping datasets to a set of non-linear coherent states, the process of encoding inputs in quantum states as a non-linear feature map is re-interpreted. As a resu…
Robustness analytics to data heterogeneity in edge computing
Jia Qian, Lars Kai Hansen, Xenofon Fafoutis +2
Federated Learning is a framework that jointly trains a model \textit{with} complete knowledge on a remotely placed centralized server, but \textit{without} the requirement of acce…
Quantum-like Structure in Multidimensional Relevance Judgements
Sagar Uprety, Prayag Tiwari, Shahram Dehdashti +4
A large number of studies in cognitive science have revealed that probabilistic outcomes of certain human decisions do not agree with the axioms of classical probability theory. Th…
Binary Classifier Inspired by Quantum Theory
Prayag Tiwari, Massimo Melucci
Machine Learning (ML) helps us to recognize patterns from raw data. ML is used in numerous domains i.e. biomedical, agricultural, food technology, etc. Despite recent technological…
Multi-class Classification Model Inspired by Quantum Detection Theory
Prayag Tiwari, Massimo Melucci
Machine Learning has become very famous currently which assist in identifying the patterns from the raw data. Technological advancement has led to substantial improvement in Machin…