Results 21 to 30 of about 23,233,852 (373)

Semi-Supervised Learning Based on Generative Adversarial Network and Its Applied to Lithology Recognition

IEEE Access, 2019
Lithology recognition is an essential part of reservoir parameter prediction. Compared to conventional algorithms, deep learning that needs a large amount of training data as support can extract features automatically.
Guohe Li, Yinghan Qiao, Yifeng Zheng, Ying Li, Weijiang Wu   +4 more
doaj   +1 more source

Re-mining item associations: methodology and a case study in apparel retailing [PDF]

, 2010
Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items.
Atan, Tankut, Demiriz, Ayhan, Ertek, Gurdal, Ertek, Gürdal, Kula, Ufuk   +4 more
core   +1 more source

Prediction of Inbound and Outbound Passenger Flow in Urban Rail Transit Based on Spatio-Temporal Attention Residual Network

Applied Sciences, 2023
Passenger flow prediction is a critical approach to ensure the effective functioning of urban rail transit. However, there are few studies that combine multiple influencing factors for short-term passenger flow prediction.
Jun Yang, Xueru Dong, Huifan Yang, Xiao Han, Yan Wang, Jiayue Chen   +5 more
doaj   +1 more source

Crowd counting via Multi-Scale Adversarial Convolutional Neural Networks

Journal of Intelligent Systems, 2020
The purpose of crowd counting is to estimate the number of pedestrians in crowd images. Crowd counting or density estimation is an extremely challenging task in computer vision, due to large scale variations and dense scene.
Zhu Liping, Zhang Hong, Ali Sikandar, Yang Baoli, Li Chengyang   +4 more
doaj   +1 more source

Immersive cultural heritage digital documentation and information service for historical figure metaverse: a case of Zhu Xi, Song Dynasty, China

Heritage Science, 2022
Cultural heritage is closely linked with individual historical figures, who become a key focus for cultural tourism. Confucianism laid the foundation for much of Chinese civilization, and Confucius and Mencius have been studied extensively and have been ...
Zhanling Fan, Chongcheng Chen, Hongyu Huang   +2 more
doaj   +1 more source

Data mining in radiology [PDF]

Indian Journal of Radiology and Imaging, 2014
AbstractData mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized
Amit Kharat, Vilas M Kulkarni, Amarjit Singh, Digish Shah   +3 more
openaire   +4 more sources

Brief introduction of medical database and data mining technology in big data era

Journal of Evidence-Based Medicine, 2020
Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results.
Jin Yang, Yuan-jie Li, Qingqing Liu, Li Li, Aozi Feng, Tianyi Wang, Shuai Zheng, Anding Xu, Jun Lyu   +8 more
semanticscholar   +1 more source

An Improved Slime Mold Algorithm and its Application for Optimal Operation of Cascade Hydropower Stations

IEEE Access, 2020
A recently modern stochastic optimization algorithm has been developed by observing the life of slime mold physarum polycephalum in nature. The algorithm is called the slime mold algorithm (SMA) with an excellent exploratory capacity and exploitation ...
Trong-The Nguyen, Hong-Jiang Wang, Thi-Kien Dao, Jeng-Shyang Pan, Jian-Hua Liu, Shaowei Weng   +5 more
doaj   +1 more source

HMD-Net: A Vehicle Hazmat Marker Detection Benchmark

Entropy, 2022
Vehicles carrying hazardous material (hazmat) are severe threats to the safety of highway transportation, and a model that can automatically recognize hazmat markers installed or attached on vehicles is essential for intelligent management systems ...
Lei Jia, Jianzhu Wang, Tianyuan Wang, Xiaobao Li, Haomin Yu, Qingyong Li   +5 more
doaj   +1 more source

Deep Learning for Spatio-Temporal Data Mining: A Survey [PDF]

IEEE Transactions on Knowledge and Data Engineering, 2019
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays.
Senzhang Wang, Jiannong Cao, Philip S. Yu   +2 more
semanticscholar   +1 more source