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Found 21 papers, 2 papers with code
Towards Effective Image Forensics via A Novel Computationally Efficient Framework and A New Image Splice Dataset
Secondly, a novel Spatio-Compression Lightweight Splice Detection Framework is proposed for accurate splice detection with minimum computational cost.
A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler
In this work, a novel, "Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler" has been proposed.
Datasets, Clues and State-of-the-Arts for Multimedia Forensics: An Extensive Review
Top results achieved on benchmark datasets, comparison of deep learning approaches against traditional methods and critical insights from the recent tampering detection methods are also discussed.
DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)
Influence Maximization is the task of selecting optimal nodes maximising the influence spread in social networks.
Optimizing Electric Vehicle Efficiency with Real-Time Telemetry using Machine Learning
In the contemporary world with degrading natural resources, the urgency of energy efficiency has become imperative due to the conservation and environmental safeguarding.
Adversarial Adaptation for French Named Entity Recognition
We propose a Transformer-based NER approach for French, using adversarial adaptation to similar domain or general corpora to improve feature extraction and enable better generalization.
Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora
Named Entity Recognition (NER) involves the identification and classification of named entities in unstructured text into predefined classes.
An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning
Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance.
Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation
Recent works on fake news detection have shown the efficacy of using emotions as a feature or emotions-based features for improved performance.
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning
We further analyze the performance of our multi-task approach for fake news detection in cross-domain settings to verify its efficacy for better generalization across datasets, and to verify that emotions act as a domain-independent feature.
A Spreader Ranking Algorithm for Extremely Low-budget Influence Maximization in Social Networks using Community Bridge Nodes
In this work, we propose a community structures-based approach, which employs a K-Shell algorithm in order to generate a score for the connections between seed nodes and communities for low-budget scenarios.
An Automated Multi-Web Platform Voting Framework to Predict Misleading Information Proliferated during COVID-19 Outbreak using Ensemble Method
The four sets of features based on the content, linguistics/semantic cues, similarity, and sentiments gathered from web-platforms and voting are applied to validate the news.
Multilevel profiling of situation and dialogue-based deep networks for movie genre classification using movie trailers
Short duration movie trailers provide useful insights about the movie as video content consists of the cognitive and the affective level features.
Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition
We extract shallow features from the 3D images, and deep features using Convolutional Neural Networks (CNN) from the transformed 2D images.
3D Facial Expression Recognition
Facial Expression Recognition
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Person Re-Identification using Deep Learning Networks: A Systematic Review
This review deals with the latest state-of-the-art deep learning based approaches for person re-identification.
A Deep Multi-Level Attentive network for Multimodal Sentiment Analysis
Then we model the correlation between the image regions and semantics of the word by extracting the textual features related to the bi-attentive visual features by applying semantic attention.
Multimodal Sentiment Analysis
Multimedia
A Deep Language-independent Network to analyze the impact of COVID-19 on the World via Sentiment Analysis
In this paper, we extract and study the opinion of people from the top five worst affected countries by the virus, namely USA, Brazil, India, Russia, and South Africa.
View-invariant Deep Architecture for Human Action Recognition using late fusion
We propose a view-invariant deep human action recognition framework, which is a novel integration of two important action cues: motion and shape temporal dynamics (STD).
Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues
There exist a wide range of intra class variations of the same actions and inter class similarity among the actions, at the same time, which makes the action recognition in videos very challenging.
A Hybrid Framework for Action Recognition in Low-Quality Video Sequences
Vision-based activity recognition is essential for security, monitoring and surveillance applications.
A Deep Structure of Person Re-Identification using Multi-Level Gaussian Models
Person re-identification is being widely used in the forensic, and security and surveillance system, but person re-identification is a challenging task in real life scenario.
