Results 31 to 40 of about 6,008 (208)

Inter-Personal Relation Extraction Model Based on Bidirectional GRU and Attention Mechanism [PDF]

, 2019
Inter-Personal Relationship Extraction is an important part of knowledge extraction and is also the fundamental work of constructing the knowledge graph of people's relationships.
Li, Gangmin, Dai, Zhenjin, Gangmin Li, Wang, Xutao, Zhenjin Dai, Ni, Pin, Yuming Li, Pin Ni, Xutao Wang, Li, Yuming   +9 more
core   +1 more source

LSTM vs. GRU vs. Bidirectional RNN for script generation

CoRR, 2019
Scripts are an important part of any TV series. They narrate movements, actions and expressions of characters. In this paper, a case study is presented on how different sequence to sequence deep learning models perform in the task of generating new conversations between characters as well as new scenarios on the basis of a script (previous ...
Sanidhya Mangal, Poorva Joshi, Rahul Modak   +2 more
openaire   +2 more sources

Visual field prediction using a deep bidirectional gated recurrent unit network model

Scientific Reports, 2023
Although deep learning architecture has been used to process sequential data, only a few studies have explored the usefulness of deep learning algorithms to detect glaucoma progression.
Hwayeong Kim, Jiwoong Lee, Sangwoo Moon, Sangil Kim, Taehyeong Kim, Sang Wook Jin, Jung Lim Kim, Jonghoon Shin, Seung Uk Lee, Geunsoo Jang, Yuanmeng Hu, Jeong Rye Park   +11 more
doaj   +1 more source

A Novel Feature Representation for Prediction of Global Horizontal Irradiance Using a Bidirectional Model

Machine Learning and Knowledge Extraction, 2021
Complex weather conditions—in particular clouds—leads to uncertainty in photovoltaic (PV) systems, which makes solar energy prediction very difficult.
Sourav Malakar, Saptarsi Goswami, Bhaswati Ganguli, Amlan Chakrabarti, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj   +6 more
doaj   +1 more source

The Analysis of Deep Learning Recurrent Neural Network in English Grading Under the Internet of Things

IEEE Access
This work aims to investigate the use of the Recurrent Neural Network (RNN) in automated English grading. In order to achieve this, this work first constructs an automated English grading system based on the Internet of Things (IoT).
Dandan Li, Wenling Li, Yanmei Zhao, Xutao Liu   +3 more
doaj   +1 more source

An intelligent operation ticket check method of power grid dispatch based on semantic analysis

Zhejiang dianli, 2022
For automatic and intelligent check of operation ticket for power grid scheduling， a scheduling operation ticket checking and analysis method based on bidirectional GRU （gated recurrent unit） neural networks and multiple verification rules is proposed ...
ZHENG Junxiang, LI Huile, HUANG Datie, SUN Jingliao, LU Yan   +4 more
doaj   +1 more source

Medical Entity Relation Recognition Combining Bidirectional GRU and Attention [PDF]

Jisuanji gongcheng, 2020
Most of existing methods for entity relationship recognition take a single sentence as processing unit,and fail to address tagging errors of entity relationships in the training corpus.Also,they cannot make full use of the mutual reinforcement of ...
ZHANG Zhichang, ZHOU Tong, ZHANG Ruifang, ZHANG Minyu
doaj   +1 more source

Comparative Deep Learning Analysis: Unveiling the Power of LSTM, BiLSTM, GRU, and BiGRU for Agricultural Stock Price Forecasting on the Indonesian Stock Exchange

Jurnal Teknologi dan Sistem Informasi
This study aims to analyze the performance of deep learning algorithms in predicting agricultural sector stock prices on the Indonesia Stock Exchange (IDX) by comparing four models: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated ...
Muhammad Fadhlurrahman, Armin Darmawan
doaj   +1 more source

Three-dimensional Softmax Mechanism Guided Bidirectional GRU Networks for Hyperspectral Remote Sensing Image Classification

, 2023
Hyperspectral data is a valuable source of both spectral and spatial information. However, to enhance the classification accuracy of hyperspectral image features, it is crucial to capture the spatial spectral features of image elements.
Wu, Guoqiang, Achyut Shankar, Ning, Xin, Xin Ning, Hengmin Zhang, Shankar, Achyut, Luyang Hou, Hou, Luyang, Zhang, Hengmin, He, Feng, Guoqiang Wu, Feng He   +11 more
core   +1 more source

Spatial-Temporal Analysis of Earthquakes in Indonesia with Deep Learning Models: Performance Evaluation of CNN, LSTM, and Hybrid CNN-GRU

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Indonesia, located along the Pacific Ring of Fire, experiences high seismic activity with over 6,000 earthquakes annually. Accurate earthquake prediction remains a major challenge because of the complexity of geological dynamics and limitations of ...
Susandri Susandri, Fajrizal Fajrizal, Feldiansyah Bakri Nasution   +2 more
doaj   +1 more source