Search Results - "Contractive Autoencoder"

Deep embedding clustering based on contractive autoencoder by Diallo, Bassoma, Hu, Jie, Li, Tianrui, Khan, Ghufran Ahmad, Liang, Xinyan, Zhao, Yimiao

“…Clustering large and high-dimensional document data has got a great interest. However, current clustering algorithms lack efficient representation learning…”
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An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder by Shen, Changqing, Qi, Yumei, Wang, Jun, Cai, Gaigai, Zhu, Zhongkui

“…Fault diagnosis of rotating machinery is vital to improve the security and reliability as well as avoid serious accidents. For instance, robust fault features…”
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Deep Learning and Superpixel Feature Extraction Based on Contractive Autoencoder for Change Detection in SAR Images by Lv, Ning, Chen, Chen, Qiu, Tie, Sangaiah, Arun Kumar

“…Image segmentation based on superpixel is used in urban and land cover change detection for fast locating region of interest. However, the segmentation…”
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Multimodal video classification with stacked contractive autoencoders by Liu, Yanan, Feng, Xiaoqing, Zhou, Zhiguang

“…In this paper we propose a multimodal feature learning mechanism based on deep networks (i.e., stacked contractive autoencoders) for video classification…”
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A Hybrid Deep Contractive Autoencoder and Restricted Boltzmann Machine Approach to Differentiate Representation of Female Brain Disorder by M.Mahmoud, Abeer, Alrowais, Fadwa, Karamti, Hanen

“…Deep Learning approach dragged the full attention of researcher in medical images due to their superior literature reported success and promising directions…”
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Deep Supervised and Contractive Neural Network for SAR Image Classification by Geng, Jie, Wang, Hongyu, Fan, Jianchao, Ma, Xiaorui

“…The classification of a synthetic aperture radar (SAR) image is a significant yet challenging task, due to the presence of speckle noises and the absence of…”
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Pilots' Fatigue Status Recognition Using Deep Contractive Autoencoder Network by Wu, Edmond Q., Peng, X. Y., Zhang, Caizhi Z., Lin, J. X., Sheng, Richard S. F.

“…The evaluation of pilots' fatigue status is of substantial significance in aviation safety, which faces two major issues. They are how to get the fatigue…”
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Robust feature learning using contractive autoencoders for multi-omics clustering in cancer subtyping by Guo, Mengke, Ye, Xiucai, Huang, Dong, Sakurai, Tetsuya

“…•We propose a novel multi-omics framework using contractive autoencoder for robust feature extraction.•Cox regression integrates survival analysis to identify…”
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Zero-day attack detection with a Dynamic-Weighted Contractive Autoencoder and GAN-based evaluation by Singha, M. Franckie, Patgiri, Ripon, Shamsi, Zeba, Singh, Laiphrakpam Dolendro

“…Anomaly detection, which has faced quite a challenge in zero-day attacks whose nature is novel and unpredictable, shall be addressed here. This research…”
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Learning 3D faces from 2D images via Stacked Contractive Autoencoder by Zhang, Jian, Li, Ke, Liang, Yun, Li, Na

“…3D face reconstruction from a 2D face image has been found important to various applications such as face detection and recognition because a 3D face provides…”
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Leveraging Contractive Autoencoders for Time-Efficient Rare Cyberattack Detection by Danasabe, Abubakar, Kaleem, Zeeshan, Muhammad, Afaq, El-Maleh, Aiman, Yuen, Chau, Jamalipour, Abbas

“…The rapid adoption of cloud computing has introduced critical security challenges in the cloud, with evolving cyberattacks exposing vulnerabilities in…”
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A Hybrid Deep Learning and Model Predictive Control Framework for Wind Farm Frequency Regulation by Ji, Ziyang, Zhang, Jie, Du, Keke, Zhou, Tao

“…To enhance wind farm frequency regulation in renewable-dominant power systems, this paper proposes a bi-level hybrid framework integrating deep learning and…”
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Enhanced autoencoder-based fraud detection: a novel approach with noise factor encoding and SMOTE by Çakır, Mert Yılmaz, Şirin, Yahya

“…Fraud detection is a critical task across various domains, requiring accurate identification of fraudulent activities within vast arrays of transactional data…”
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SCDD: a novel single-cell RNA-seq imputation method with diffusion and denoising by Liu, Jian, Pan, Yichen, Ruan, Zhihan, Guo, Jun

“…Abstract Single-cell sequencing technologies are widely used to discover the evolutionary relationships and the differences in cells. Since dropout events may…”
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Enhanced prediction of stock markets using a novel deep learning model PLSTM-TAL in urbanized smart cities by Latif, Saima, Javaid, Nadeem, Aslam, Faheem, Aldegheishem, Abdulaziz, Alrajeh, Nabil, Bouk, Safdar Hussain

“…Accurate predictions of stock markets are important for investors and other stakeholders of the equity markets to formulate profitable investment strategies…”
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IUAutoTimeSVD++: A Hybrid Temporal Recommender System Integrating Item and User Features Using a Contractive Autoencoder by Azri, Abdelghani, Haddi, Adil, Allali, Hakim

“…Collaborative filtering (CF), a fundamental technique in personalized Recommender Systems, operates by leveraging user–item preference interactions. Matrix…”
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Comparative Analysis of Unsupervised and Supervised Autoencoders for Nuclei Classification in Clear Cell Renal Cell Carcinoma Images by Javadian, Fatemeh, Aminparast, Zahra, Stegmaier, Johannes, Jose, Abin

“…This study explores the application of supervised and unsupervised autoencoders (AEs) to automate nuclei classification in clear cell renal cell carcinoma…”
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Improved Combined Inertial Control of Wind Turbine Based on CAE and DNN for Temporary Frequency Support by Ji, Ziyang, Zhang, Jie, Liu, Yi, Zhou, Tao

“…With the continuous and large-scale development of renewable energy, there is a prominent decrease in the level of inertia in new power systems. This decrease…”
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Software Defect Prediction Based on Stacked Contractive Autoencoder and Multi-objective Optimization by Zhang, Nana, Zhu, Kun, Ying, Shi, Wang, Xu

“…Software defect prediction plays an important role in software quality assurance. However, the performance of the prediction model is susceptible to the…”
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Hyperspectral Data Feature Extraction Using Deep Learning Hybrid Model by Jiang, Xinhua, Xue, Heru, Zhang, Lina, Gao, Xiaojing, Zhou, Yanqing, Bai, Jie

“…The original hyperspectral data served as the initial features has the characteristics of high dimension and redundancy, which is not suitable for the…”
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