TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
GitHub

Pytorch 1.0 port of the AWD LSTM Language model

Next, decide whether to use the QRNN or the LSTM as the underlying recurrent neural network model. The QRNN is many times faster than even Nvidia's cuDNN optimized LSTM (and dozens of times faster ...
Reuters

India enforces four new labour codes in major overhaul of worker rules

NEW DELHI, Nov 21 (Reuters) - India on Friday implemented four new labour codes, pushing ahead with the biggest overhaul of workers' laws in decades as Prime Minister Narendra Modi’s government says ...
GitHub

Multimodal Emotion Recognition in Conversations via Graph Structure Learning

Python 3.10.13 PyTorch 1.13.0 torch_geometric 2.5.2 torch-cluster 1.6.1 torch-scatter 2.1.1 torch-sparse 0.6.17 torch-spline-conv 1.2.2 sparsemax 0.1.9 CUDA 11.7 Train RIGSL using the MELD dataset.
Hosted on MSN

Predicting Emojis with LSTM in TensorFlow Full Walkthrough Guide

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
IEEE

Integrating Deep Learning and Python for Effective Sign Language Recognition

Abstract: The advancement in technology has improved the accessibility of communications for a person with hearing impairment significantly. A full implementation approach for sign language ...
Scientific Research Publishing

Waqas, M., & Humphries, U. W. (2024). A Critical Review of RNN and LSTM Variants in Hydrological Time Series Predictions. MethodsX, 13, 102946.

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...
IEEE

Enhancing Security Through the Implementation of Deep Learning Techniques GRU and LSTM for Intelligent Intrusion Detection

Abstract: Anomaly-based intelligent intrusion detection systems (IDS) employ advanced algorithms and deep learning (DL) techniques to monitor network traffic, system behavior, and user activities in ...