147 citations · 304 across the 35 of their papers we have counts for
36 papers
HCIG: A Hierarchical Cross-Modal Incongruity Graph Network for Multimodal Sarcasm and Cyberbullying Detection
Bhavana Verma, Priyanka Meel, Dinesh Kumar Vishwakarma
Multimodal sarcasm and cyberbullying detection remain challenging because the intended meaning often emerges from incongruity between textual and visual information rather than fro…
MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Framework
Anusha Chhabra, Dinesh Kumar Vishwakarma
Social media has a significant impact on people's lives. Hate speech on social media has emerged as one of society's most serious issues in recent years. Text and pictures are two…
Hate Content Detection via Novel Pre-Processing Sequencing and Ensemble Methods
Anusha Chhabra, Dinesh Kumar Vishwakarma
Social media, particularly Twitter, has seen a significant increase in incidents like trolling and hate speech. Thus, identifying hate speech is the need of the hour. This paper in…
A Noise and Edge extraction-based dual-branch method for Shallowfake and Deepfake Localization
Deepak Dagar, Dinesh Kumar Vishwakarma
The trustworthiness of multimedia is being increasingly evaluated by advanced Image Manipulation Localization (IML) techniques, resulting in the emergence of the IML field. An effe…
Target-Dependent Multimodal Sentiment Analysis Via Employing Visual-to Emotional-Caption Translation Network using Visual-Caption Pairs
Ananya Pandey, Dinesh Kumar Vishwakarma
The natural language processing and multimedia field has seen a notable surge in interest in multimodal sentiment recognition. Hence, this study aims to employ Target-Dependent Mul…
VyAnG-Net: A Novel Multi-Modal Sarcasm Recognition Model by Uncovering Visual, Acoustic and Glossary Features
Ananya Pandey, Dinesh Kumar Vishwakarma
Various linguistic and non-linguistic clues, such as excessive emphasis on a word, a shift in the tone of voice, or an awkward expression, frequently convey sarcasm. The computer v…
Modelling Visual Semantics via Image Captioning to extract Enhanced Multi-Level Cross-Modal Semantic Incongruity Representation with Attention for Multimodal Sarcasm Detection
Sajal Aggarwal, Ananya Pandey, Dinesh Kumar Vishwakarma
Sarcasm is a type of irony, characterized by an inherent mismatch between the literal interpretation and the intended connotation. Though sarcasm detection in text has been extensi…
Contrastive Learning-based Multi Modal Architecture for Emoticon Prediction by Employing Image-Text Pairs
Ananya Pandey, Dinesh Kumar Vishwakarma
The emoticons are symbolic representations that generally accompany the textual content to visually enhance or summarize the true intention of a written message. Although widely ut…
Tex-ViT: A Generalizable, Robust, Texture-based dual-branch cross-attention deepfake detector
Deepak Dagar, Dinesh Kumar Vishwakarma
Deepfakes, which employ GAN to produce highly realistic facial modification, are widely regarded as the prevailing method. Traditional CNN have been able to identify bogus media, b…
Datasets, Clues and State-of-the-Arts for Multimedia Forensics: An Extensive Review
Ankit Yadav, Dinesh Kumar Vishwakarma
With the large chunks of social media data being created daily and the parallel rise of realistic multimedia tampering methods, detecting and localising tampering in images and vid…
Towards Effective Image Forensics via A Novel Computationally Efficient Framework and A New Image Splice Dataset
Ankit Yadav, Dinesh Kumar Vishwakarma
Splice detection models are the need of the hour since splice manipulations can be used to mislead, spread rumors and create disharmony in society. However, there is a severe lack…
A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler
Ankit Yadav, Dinesh Kumar Vishwakarma
Image splice manipulation presents a severe challenge in today's society. With easy access to image manipulation tools, it is easier than ever to modify images that can mislead ind…
DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)
Aryaman Rao, Parth Singh, Dinesh Kumar Vishwakarma +1
Influence Maximization is the task of selecting optimal nodes maximising the influence spread in social networks. This study proposes a Discretized Quantum-based Salp Swarm Algorit…
Optimizing Electric Vehicle Efficiency with Real-Time Telemetry using Machine Learning
Aryaman Rao, Harshit Gupta, Parth Singh +3
In the contemporary world with degrading natural resources, the urgency of energy efficiency has become imperative due to the conservation and environmental safeguarding. Therefore…
Adversarial Adaptation for French Named Entity Recognition
Arjun Choudhry, Inder Khatri, Pankaj Gupta +4
Named Entity Recognition (NER) is the task of identifying and classifying named entities in large-scale texts into predefined classes. NER in French and other relatively limited-re…
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning
Arjun Choudhry, Inder Khatri, Minni Jain +1
Social networking sites, blogs, and online articles are instant sources of news for internet users globally. However, in the absence of strict regulations mandating the genuineness…
Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora
Arjun Choudhry, Pankaj Gupta, Inder Khatri +4
Named Entity Recognition (NER) involves the identification and classification of named entities in unstructured text into predefined classes. NER in languages with limited resource…
CKS: A Community-based K-shell Decomposition Approach using Community Bridge Nodes for Influence Maximization
Inder Khatri, Aaryan Gupta, Arjun Choudhry +3
Social networks have enabled user-specific advertisements and recommendations on their platforms, which puts a significant focus on Influence Maximisation (IM) for target advertisi…
An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning
Arkajyoti Chakraborty, Inder Khatri, Arjun Choudhry +3
Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance. However, the cross-domain impact of emotion-guided features for…
Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation
Arjun Choudhry, Inder Khatri, Arkajyoti Chakraborty +2
Recent works on fake news detection have shown the efficacy of using emotions as a feature or emotions-based features for improved performance. However, the impact of these emotion…
Influence Maximization in Social Networks using Discretized Harris Hawks Optimization Algorithm and Neighbour Scout Strategy
Inder Khatri, Arjun Choudhry, Aryaman Rao +3
Influence Maximization (IM) is the task of determining k optimal influential nodes in a social network to maximize the influence spread using a propagation model. IM is a prominent…
Clickbait in YouTube Prevention, Detection and Analysis of the Bait using Ensemble Learning
Peya Mowar, Mini Jain, Ruchika Goel +1
Unscrupulous content creators on YouTube employ deceptive techniques such as spam and clickbait to reach a broad audience and trick users into clicking on their videos to increase…
Fake News Detection using Semi-Supervised Graph Convolutional Network
Priyanka Meel, Dinesh Kumar Vishwakarma
Social media becomes the central way for people to obtain and utilise news, due to its rapidness and inexpensive value of data distribution. Though, such features of social media p…
Multi-modal Fusion using Fine-tuned Self-attention and Transfer Learning for Veracity Analysis of Web Information
Priyanka Meel, Dinesh Kumar Vishwakarma
The nuisance of misinformation and fake news has escalated many folds since the advent of online social networks. Human consciousness and decision-making capabilities are negativel…