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检索条件"主题词=sparse AutoEncoder"
252 条 记 录,以下是41-50 订阅
排序:
Self-adaptive weighted synthesised local directional pattern integrating with sparse autoencoder for expression recognition based on improved multiple kernel learning strategy
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IET COMPUTER VISION 2020年 第3期14卷 73-83页
作者: Du, Lingshuang Wu, Yongbo Hu, Haifeng Wang, Weixuan Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou Peoples R China
This study presents a novel method for solving facial expression recognition (FER) tasks which uses a self-adaptive weighted synthesised local directional pattern (SW-SLDP) descriptor integrating sparse autoencoder (S... 详细信息
来源: 评论
sparse autoencoder for social image understanding
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NEUROCOMPUTING 2019年 369卷 122-133页
作者: Liu, Jianran Wang, Shiping Yang, Wenyuan Minnan Normal Univ Fujian Key Lab Granular Comp & Applicat Zhangzhou 363000 Peoples R China Fuzhou Univ Fujian Prov Key Lab Network Comp & Intelligent In Fuzhou 350000 Fujian Peoples R China
The rapid increase of social media images has made organizing these resources effectively a huge problem. Labeling unlabeled images becomes the crucial division of social image understanding. However, the enhancement ... 详细信息
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ASD-SAENet: A sparse autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data
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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2021年 15卷 654315页
作者: Almuqhim, Fahad Saeed, Fahad Florida Int Univ Knight Fdn Sch Comp & Informat Sci Miami FL 33199 USA
Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder which is characterized by impaired communication, and limited social interactions. The shortcomings of current clinical approaches which are... 详细信息
来源: 评论
Deep sparse autoencoder prediction model based on adversarial learning for cross-domain recommendations
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KNOWLEDGE-BASED SYSTEMS 2021年 220卷 106948-106948页
作者: Li, Yakun Ren, Jiadong Liu, Jiaomin Chang, Yixin Yanshan Univ Coll Informat Sci & Engn Qinhuangdao Hebei Peoples R China Key Lab Comp Virtual Technol & Syst Integrat Hebe Qinhuangdao Hebei Peoples R China
Online recommender systems generally suffer from severe data sparsity problems, and this are particularly prevalent in newly launched systems that do not have sufficient amounts of data. Cross-domain recommendations c... 详细信息
来源: 评论
Fault Diagnosis Based on Batch-normalized Stacked sparse autoencoder  39
Fault Diagnosis Based on Batch-normalized Stacked Sparse Aut...
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39th Chinese Control Conference (CCC)
作者: Liu Xiaozhi Gao Yang Yang Yinghua Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China
A fault diagnosis method based on batch-normalization stacked sparse autoencoder (SSAE) is presented in this paper. This paper use the autoencoder to extract features for fault diagnosis on account of its good perform... 详细信息
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sparse autoencoder Based Manifold Analyzer Model of Multi-Angle Target Feature
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IEEE ACCESS 2020年 8卷 153250-153263页
作者: Chen, Xiuyuan Peng, Xiyuan Li, Jun-Bao Huo, Chaoying Harbin Inst Technol Harbin 150080 Peoples R China Harbin Inst Technol Sch Elect & Informat Engn Harbin 150080 Peoples R China Sci & Technol Electromagnet Scattering Lab Beijing 100039 Peoples R China
Automatic target recognition (ATR) has always been an important research topic, and the performance is affected by feature extraction. High-resolution range profiles (HRRP) contains structural information of target fr... 详细信息
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sparse autoencoder with Attention Mechanism for Speech Emotion Recognition  1
Sparse Autoencoder with Attention Mechanism for Speech Emoti...
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1st IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
作者: Sun, Ting-Wei Wu, An-Yeu (Andy) Natl Taiwan Univ Grad Inst Elect Engn Taipei Taiwan
There has been a lot of previous works on speech emotion with machine learning method. However, most of them rely on the effectiveness of labelled speech data. In this paper, we propose a novel algorithm which combine... 详细信息
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EndNet: sparse autoencoder Network for Endmember Extraction and Hyperspectral Unmixing
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2019年 第1期57卷 482-496页
作者: Ozkan, Savas Kaya, Berk Akar, Gozde Bozdagi TUBITAK Space Technol Res Inst Image Proc Dept TR-06800 Ankara Turkey Middle East Tech Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey
Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sens... 详细信息
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A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion
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EVOLUTIONARY INTELLIGENCE 2021年 第1期14卷 133-149页
作者: Ghosh, Swarup Kr Biswas, Biswajit Ghosh, Anupam Maulana Abul Kalam Azad Univ Technol Kolkata 700068 India Univ Calcutta Kolkata 700098 India Netaji Subhash Engn Coll Kolkata 700152 India
This paper proposes a deep unsupervised learning based denoising autoencoder model for the restoration of degraded mammogram with visual interpretation of breast lumps or lesion in mammography images (called SSDAE). T... 详细信息
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Prediction of aptamer-protein interacting pairs based on sparse autoencoder feature extraction and an ensemble classifier
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MATHEMATICAL BIOSCIENCES 2019年 311卷 103-108页
作者: Yang Qing Jia Cangzhi Li Taoying Dalian Maritime Univ Inst Environm Syst Biol Coll Environm & Engn 1 Linghai Rd Dalian 116026 Peoples R China Dalian Maritime Univ Sch Sci 1 Linghai Rd Dalian 116026 Peoples R China Dalian Maritime Univ Dept Maritime Econ & Management 1 Linghai Rd Dalian 116026 Peoples R China
Aptamer-protein interacting pairs play important roles in physiological functions and structural characterization. Identifying aptamer-protein interacting pairs is challenging and limited, despite of the tremendous ap... 详细信息
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