Abstract: Accurate prediction of blood glucose levels is crucial for automated treatment in diabetic patients. This study proposes a blood glucose prediction model based on an improved attention ...

This project implements a from-scratch Encoder-Decoder LSTM model for English to French machine translation using PyTorch. The model uses a fixed context vector approach without attention mechanism, ...

This research paper presents a proactive approach to congestion control in IoT networks using an encoder–decoder LSTM (ED-LSTM) model to predict packet loss ratios ahead of time. By forecasting ...

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...

Long short-term memory (LSTM) networks have become indispensable tools in hydrological modeling due to their ability to capture long-term dependencies, handle non-linear relationships, and integrate ...

Abstract: In this paper we present LSTM based neural network architectures for determining the part of speech (POS) tags for Romanian words. LSTM networks combined with fully-connected output layers ...

ABSTRACT: With technology advances and human requirements increasing, human-computer interaction plays an important role in our daily lives. Among these interactions, gesture-based recognition offers ...

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