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Found 15 papers, 2 papers with code
BanglaHateBERT: BERT for Abusive Language Detection in Bengali
This paper introduces BanglaHateBERT, a retrained BERT model for abusive language detection in Bengali.
Finnish Hate-Speech Detection on Social Media Using CNN and FinBERT
The majority of this research has concentrated on English, although one notices the emergence of multilingual detection tools such as multilingual-BERT (mBERT).
Data Expansion Using WordNet-based Semantic Expansion and Word Disambiguation for Cyberbullying Detection
Automatic identification of cyberbullying from textual content is known to be a challenging task.
A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMs
The surge of interest in data augmentation within the realm of NLP has been driven by the need to address challenges posed by hate speech domains, the dynamic nature of social media vocabulary, and the demands for large-scale neural networks requiring extensive training data.
Cross-Linguistic Offensive Language Detection: BERT-Based Analysis of Bengali, Assamese, & Bodo Conversational Hateful Content from Social Media
The primary emphasis is placed on the meticulous detection of hate speech within the linguistic domains of Bengali, Assamese, and Bodo, forming the framework for Task 4: Annihilate Hates.
Semi-Supervised learning for Face Anti-Spoofing using Apex frame
Conventional feature extraction techniques in the face anti-spoofing domain either analyze the entire video sequence or focus on a specific segment to improve model performance.
Saliency-based Video Summarization for Face Anti-spoofing
Inspired by the visual saliency theory, we present a video summarization method for face anti-spoofing detection that aims to enhance the performance and efficiency of deep learning models by leveraging visual saliency.
Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofing
Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control systems, mobile payments, and identity verification systems.
Domain Generalization via Ensemble Stacking for Face Presentation Attack Detection
The latter combines the predictions from the base models, leveraging their complementary information to better handle unseen target domains and enhance the overall performance.
Face Anti-Spoofing from the Perspective of Data Sampling
In particular, the proposed scheme provides a much lower error (from 15. 2% to 6. 7% on CASIA-FASD and 5. 9% to 4. 9% on Replay-Attack) compared to baselines in cross-database scenarios.
Self-Supervised Face Presentation Attack Detection with Dynamic Grayscale Snippets
To achieve this, we exploit the temporal consistency based on three RGB frames which are acquired at three different times in the video sequence.
DziriBERT: a Pre-trained Language Model for the Algerian Dialect
The obtained results show that pre-training a dedicated model on a small dataset (150 MB) can outperform existing models that have been trained on much more data (hundreds of GB).
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection
With proliferation of user generated contents in social media platforms, establishing mechanisms to automatically identify toxic and abusive content becomes a prime concern for regulators, researchers, and society.
A systematic review of Hate Speech automatic detection using Natural Language Processing
With the multiplication of social media platforms, which offer anonymity, easy access and online community formation, and online debate, the issue of hate speech detection and tracking becomes a growing challenge to society, individual, policy-makers and researchers.
