Results 81 to 90 of about 208,635 (216)
LSTM-GWO performance evaluation with experiment 5.
, 2022 LSTM-GWO performance evaluation with experiment 5.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Gender identification for Egyptian Arabic dialect in twitter using deep learning models
Egyptian Informatics Journal, 2020 Although the number of Arabic language writers in social media is increasing, the research work targeting Author Profiling (AP) is at the initial development phase.
Shereen ElSayed, Mona Farouk
doaj +1 more source
Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network
, 2018 A deep learning network was used to predict future blood glucose levels, as this can permit diabetes patients to take action before imminent hyperglycaemia and hypoglycaemia.
Mougiakakou, Stavroula Georgia +7 more
core +1 more source
LSTM-GWO performance evaluation with experiment 6.
, 2022 LSTM-GWO performance evaluation with experiment 6.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source
Advanced Intelligent Systems, EarlyView.Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati +3 more
wiley +1 more source
Bidirectional LSTM models for DGA classification
, 2018 The paper describes our submission to the shared task on DGA classification at DMD 2018. The approach is based on a Deep Learning architecture using bidirectional LSTM neural networks.
Giuseppe Attardi, Daniele Sartiano
core +1 more source
Research on Diaphragm Pump Fault Diagnosis Method Based on Res‐DCB‐Net
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT Nonstationary pressure pulsation signals of diaphragm pumps contain strong background noise and coupled characteristics. This makes it challenging to extract incipient fault features and to decouple faults with similar physical mechanisms. To address these limitations, this paper proposes a spatiotemporal fault diagnosis model named Res‐DCB ...
Jiahui Wang +7 more
wiley +1 more source
Framewise phoneme classification with bidirectional lstm networks
, 2005 — In this paper, we present bidirectional Long Short Term Memory (LSTM) networks, and a modified, full gradient version of the LSTM learning algorithm. We evaluate bidirec-tional LSTM (BLSTM) and several other network architectures on the benchmark task ...
Graves, Alex;Schmidhuber, Jürgen +1 more
core
Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT This study aims at shedding light on the vast landscape of natural language processing (NLP) tasks used when analyzing sustainability reports or sustainability within integrated annual reports. A systematic literature review is carried out, identifying 160 studies of relevance.
Hannes Cordes
wiley +1 more source