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TOXIC COMMENT CLASSIFICATION USING BI-LSTM

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
In the age of internet and social media platforms, the problem of toxic remarks has become increasingly prominent. This research addresses the application of advanced deep learning technique, specifically C Bidirectional Long Short-Term Memory networks (Bi-LSTM), for the classification of toxic comments.
openaire +1 more source

Attention-based Binary Question Answering Using Hybrid of Bi-LSTM and Bi-GRU

مجلة بغداد للعلوم
Question Answering (QA) is a crucial aspect of Natural Language Processing (NLP) and information retrieval systems. Users usually hope to help with everyday life by teaching the program how to answer questions like a real person.
Nada Fadhil Mohammed, Israa Hadi Ali
doaj +1 more source

A CNN-Bi-LSTM pipeline and open FSW dataset for freestyle wrestling action recognition. [PDF]

Sci Rep
Rostamian M, Mottaghi A, Soryani M.
europepmc +1 more source

Advanced feature selection and temporal attention mechanisms with Bi-LSTM classifier for optimizing emotion recognition in Kashmiri speech. [PDF]

Front Artif Intell
Dar GM, Delhibabu R.
europepmc +1 more source

Pipeline Leakage Identification Based on Acoustic Sensors and EPSO-1D-CNN-Bi-LSTM Model. [PDF]

Sensors (Basel)
Wang N, Zhang K, Wang X, Peng B, Zhai S.
europepmc +1 more source

A joint CNN-Bi-LSTM-transformer architecture with SHAP explanations for multi-label arrhythmia detection from 12-lead ECGs. [PDF]

Sci Rep
Al-Bairmani MT, Yazdchi M, Nasimi F.
europepmc +1 more source

Detecting Minor Symptoms of Parkinson's Disease in the Wild Using Bi-LSTM with Attention Mechanism. [PDF]