Results 51 to 60 of about 16,939 (236)

Bidirectional Long Short-Term Memory Development for Aircraft Trajectory Prediction Applications to the UAS-S4 Ehécatl

Aerospace
The rapid advancement of unmanned aerial systems in various civilian roles necessitates improved safety measures during their operation. A key aspect of enhancing safety is effective collision avoidance, which is based on conflict detection and is ...
Seyed Mohammad Hashemi, Ruxandra Mihaela Botez, Georges Ghazi   +2 more
doaj   +1 more source

Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series

Remote Sensing, 2022
The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological behavior
Ivo Augusto Lopes Magalhães, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Anesmar Olino de Albuquerque, Potira Meirelles Hermuche, Éder Renato Merino, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães   +7 more
doaj   +1 more source

Graph-based Dependency Parsing with Bidirectional LSTM [PDF]

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2016
Dans cet article, nous proposons un modèle de réseau neuronal pour l'analyse de dépendance basée sur des graphes qui utilise LSTM bidirectionnel (BLSTM) pour capturer des informations contextuelles plus riches au lieu d'utiliser la factorisation d'ordre élevé, et permettre à notre modèle d'utiliser beaucoup moins de fonctionnalités que les travaux ...
Wenhui Wang, Baobao Chang
openaire   +1 more source

Image Captioning using Hybrid of VGG16 and Bidirectional LSTM Model

, 2022
Image captioning is one of the biggest challenges in the fields of computer vision and natural language processing. Many other studies have raised the topic of image captioning. However, the evaluation results from other studies are still low. Thus, this
Anugerah, M. Randy, Yusriansyah, Alfin, Azhar, Yufis, Fahlopy, Muhammad Al Reza   +3 more
core   +2 more sources

Detection of fake news using deep learning CNN–RNN based methods

ICT Express, 2022
Fake news is inaccurate information that is intentionally disseminated for a specific purpose. If allowed to spread, fake news can harm the political and social spheres, so several studies are conducted to detect fake news.
I. Kadek Sastrawan, I.P.A. Bayupati, Dewa Made Sri Arsa   +2 more
doaj   +1 more source

Implementasi Bidirectional LSTM untuk Analisis Sentimen Terhadap Layanan Grab Indonesia

, 2022
Grab Indonesia is one of the leading online motorcycle taxi companies in Indonesia and has a large number of customers in Indonesia. The level of customer satisfaction varies with the services provided, so there must be suggestions and complaints from ...
Firmansyah, Lutfi, Alghifari, Dloifur Rohman, Edi, Mohammad   +2 more
core   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Comparing Long Short-Term Memory (LSTM) and bidirectional LSTM deep neural networks for power consumption prediction

, 2023
Electric consumption prediction methods are investigated for many reasons, such as decision-making related to energy efficiency as well as for anticipating demand and the dynamics of the energy market.
Anderson Alvarenga de Moura Meneses, Davi Guimarães da Silva   +1 more
core   +1 more source

Chinese Sequence Labeling Based on Stack Pre-training Model

Journal of Harbin University of Science and Technology, 2022
Sequence labeling is an important task in natural language processing. In this paper, according to the relevance of tasks, we use stacking pretraining model to extract features, segment words, and name entity recognition/chunk tagging.Through in-depth ...
LIU Yu-peng, LI Guo-dong
doaj   +1 more source