Results 151 to 160 of about 10,214 (201)

A Jeap-BiLSTM Neural Network for Action Recognition

International Journal of Image and Graphics, 2023
Human action recognition in videos is an important task in computer vision with applications in fields such as surveillance, human–computer interaction, and sports analysis. However, it is a challenging task due to the complex background changes and redundancy of long-term video information.
Lunzheng Tan, Yanfei Liu, Limin Xia, Shangsheng Chen, Zhanben Zhou   +4 more
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Deep Recommendation Model Based on BiLSTM and BERT

2021
Recommendation models based on rating behavior often fail to properly deal with the problem of data sparsity, resulting in the cold-start phenomenon, which limits the recommendation effect. A model based on user behavior and semantics can better describe user preferences and item features to improve the performance of a recommender system, but is ...
Changwei Liu, Xiaowen Deng
openaire   +1 more source

Driver Drowsiness Detection: Comparative Analysis of BiLSTM and CNN+BiLSTM Architectures

Anais da X Escola Regional de Informática do Espírito Santo (ERI-ES 2025)
Driver drowsiness can negatively affect a person’s ability to stay alert, compromising not only their own safety but also the safety of others. In this work, we propose a comparison between a binary CNN+BiLSTM model and a BiLSTM model to predict whether an individual is alert or not.
Luma T. L. de Souza, Thiago M. Paixão, Richard J. M. G. Tello   +2 more
openaire   +1 more source

Relation Classification via BiLSTM-CNN

2018
In sentence-level relation classification field, both recurrent neural networks (RNN) and conventional neural networks (CNN) have won tremendous success. These methods do not rely on NLP systems like named entity recognizers (NER). However either CNN or RNN has its advantages and disadvantages for relation classification.
Lei Zhang 0049, Fusheng Xiang
openaire   +1 more source

BiLSTM-Based Models for Metaphor Detection

2018
Metaphor is a pervasive phenomenon in our daily use of natural language. Metaphor detection has been playing an important role in a variety of NLP tasks. Most existing approaches to this task rely heavily on the use of human-crafted features built from linguistic knowledge resource, which greatly limits their applicability.
Shichao Sun, Zhipeng Xie
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Using BiLSTM in Dependency Parsing for Vietnamese

Computación y Sistemas, 2018
Recently, deep learning methods have achieved good results in dependency parsing for many natural languages. In this paper, we investigate the use of bidirectional long short-term memory network models for both transition-based and graph-based dependency parsing for the Vietnamese language.
Thi Luong Nguyen, Linh Ha My, Nguyên Thi Minh Huyên, Phuong Le-Hong   +3 more
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Hybrid BiLSTM-Siamese Network for Relation Extraction

International Joint Conference on Autonomous Agents and Multiagent Systems, 2019
Relation extraction is an important processing task in knowledge graph completion. In previous approaches, it is considered to be a multi-class classification problem. In this paper, we propose a novel approach called hybrid BiLSTM-Siamese network which combines two word-level bidirectional LSTMs by a Siamese model architecture.
Zeyuan Cui, Li Pan 0001, Shijun Liu
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The Performance of LSTM and BiLSTM in Forecasting Time Series

2019 IEEE International Conference on Big Data (Big Data), 2019
Machine and deep learning-based algorithms are the emerging approaches in addressing prediction problems in time series. These techniques have been shown to produce more accurate results than conventional regression-based modeling. It has been reported that artificial Recurrent Neural Networks (RNN) with memory, such as Long Short-Term Memory (LSTM ...
Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin   +2 more
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LI3D-BiLSTM: A Lightweight Inception-3D Networks with BiLSTM for Video Action Recognition

ICCK Transactions on Emerging Topics in Artificial Intelligence
This paper proposes an improved video action recognition method, primarily consisting of three key components. Firstly, in the data preprocessing stage, we developed multi-temporal scale video frame extraction and multi-spatial scale video cropping techniques to enhance content information and standardize input formats.
Fafa Wang, Xuebo Jin, Shenglun Yi
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SW-BiLSTM: a Spark-based weighted BiLSTM model for traffic flow forecasting

Multimedia Tools and Applications, 2022
Dawen Xia, Nan Yang, Shunying Jian, Yang Hu, Huaqing Li 0001   +4 more
openaire   +1 more source