Suchergebnisse - "stacked sparse autoencoder(SSAE)"

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images von Jun Xu, Lei Xiang, Qingshan Liu, Gilmore, Hannah, Jianzhong Wu, Jinghai Tang, Madabhushi, Anant

“… Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of …”
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Improved Human Activity Recognition Using Stacked Sparse Autoencoder (SSAE) Algorithm von Aziz, Firman, Mustamin, Nurul Fathanah, Rijal, Muhammad, Tanniewa, Adam M

“… This study aims to enhance the performance of Human Activity Recognition (HAR) systems by implementing the Stacked Sparse Autoencoder (SSAE …”
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Novel Pelican Optimization Algorithm (POA) With Stacked Sparse Autoencoder (SSAE) Based IDS for Network Security von Kanimozhi, R., Neela Madheswari, A.

“… ABSTRACT Security is a crucial factor for information systems and other vital infrastructures. Ensuring robust security measures is imperative due to the …”
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Stacked Sparse Autoencoder (SSAE) based framework for nuclei patch classification on breast cancer histopathology von Jun Xu, Lei Xiang, Renlong Hang, Jianzhong Wu

“… In this paper, a Stacked Sparse Autoencoder (SSAE) based framework is presented for nuclei classification on breast cancer histopathology …”
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Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample von Saufi, Syahril Ramadhan, Ahmad, Zair Asrar Bin, Leong, Mohd Salman, Lim, Meng Hee

“… To compensate for this deficiency, a DL model based on a stacked sparse autoencoder (SSAE) model is designed to deal with limited sample data …”
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Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification von Deng, Cheng, Xue, Yumeng, Liu, Xianglong, Li, Chao, Tao, Dacheng

“… More specifically, deep joint spectral-spatial feature is first extracted through hierarchical stacked sparse autoencoder (SSAE) networks …”
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A Sleep Apnea Detection Method Based on Unsupervised Feature Learning and Single-Lead Electrocardiogram von Feng, Kaicheng, Qin, Hengji, Wu, Shan, Pan, Weifeng, Liu, Guanzheng

“… Sleep apnea (SA) is a harmful respiratory disorder that has caused widespread concern around the world. Considering that electrocardiogram (ECG)-based SA …”
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Unsupervised Spectral-Spatial Feature Learning With Stacked Sparse Autoencoder for Hyperspectral Imagery Classification von Tao, Chao, Pan, Hongbo, Li, Yansheng, Zou, Zhengrou

“… In this letter, different from traditional methods using original spectral features or handcraft spectral-spatial features, we propose to adaptively learn a …”
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Diagnosis of Interturn Short-Circuit Faults in Permanent Magnet Synchronous Motors Based on Few-Shot Learning Under a Federated Learning Framework von Zhang, Jinglin, Wang, Yanbo, Zhu, Kai, Zhang, Yi, Li, Yuanjiang

“… Its global model is updated by the local client without sharing data at each round. Considering computing resources and communication loss of multiple clients, an efficient method based on stacked sparse autoencoders (SSAEs …”
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Stacked Sparse Autoencoder in PolSAR Data Classification Using Local Spatial Information von Zhang, Lu, Ma, Wenping, Zhang, Dan

“… Among various classification techniques, the stacked sparse autoencoder (SSAE) is a kind of deep learning method that can automatically learn useful features layer by layer in an unsupervised manner …”
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Abnormal Dynamic Recognition of Space Targets from ISAR Image Sequences with SSAE-LSTM Network von Duan, Jia, Ma, Yan, Zhang, Lei, Xie, Pengfei

“… With the accommodation of the stacked sparse autoencoder (SSAE) network joint sparsity constraint, the geometrical feature flow of an ISAR image sequence is learned to represent the target dynamics concisely …”
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A Novel Two-Stage Unsupervised Fault Recognition Framework Combining Feature Extraction and Fuzzy Clustering for Collaborative AIoT von Hu, Xufeng, Li, Yibin, Jia, Lei, Qiu, Meikang

“… ) is proposed for unsupervised fault clustering in this article. DAFC amalgamates stacked sparse autoencoder (SSAE …”
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An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM von Di, Danyang, Wang, Dianchang, Fang, Hongyuan, He, Qiang, Zhou, Lifen, Chen, Xianming, Sun, Bin, Zhang, Jinping

“… •Siltation diagnosing systems of drainage pipes cannot achieve full coverage.•Generative adversarial network solves the small data sample problem.•Guided …”
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Nonlinear Generalized Predictive Control of the Crystal Diameter in CZ-Si Crystal Growth Process Based on Stacked Sparse Autoencoder von Liu, Ding, Zhang, Ni, Jiang, Lei, Zhao, Xiao-Guo, Duan, Wei-Feng

“… predictive controller (GPC) based on the stacked sparse autoencoder (SSAE) is proposed under the new control structure …”
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Online prediction of composite material drilling quality based on multi-sensor fusion von Liu, Wei, Cui, ·Jiacheng, Lu, Yongkang, Yin, Pengbo, Han, Lei, Jiang, Yingxin, Zhang, Yang

“… The Multi-sensor Fusion Long Short-Term Memory (MFLSTM) model, which incorporates a Stacked Sparse Autoencoder (SSAE …”
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Discriminative Feature Learning With Distance Constrained Stacked Sparse Autoencoder for Hyperspectral Target Detection von Shi, Yanzi, Lei, Jie, Yin, Yaping, Cao, Kailang, Li, Yunsong, Chang, Chein-I

“… Unlike supervised networks, unsupervised stacked sparse autoencoders (SSAEs) can learn deep and nonlinear features without any labeled data …”
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A denoising method for ECG signals based on CEEMDAN-TSO and stacked sparse autoencoders von Li, Shun, Li, Juan, Mao, Jiandong, Hong, Wei, Sun, Ao

“… ), Tuna Swarm Optimization (TSO), and Stacked Sparse Autoencoder (SSAE), named CEEMDAN-TSO-SSAE …”
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A packet-loss resilient protection scheme for hybrid microgrids based on Markov chain model and spline interpolation von Rameshrao, Awagan Goyal, Koley, Ebha, Ghosh, Subhojit

“… ), Markov chain-based packet loss modelling, spline interpolation and deep learning based stacked sparse autoencoder (SSAE …”
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Unsupervised Learning of 3-D Local Features From Raw Voxels Based on a Novel Permutation Voxelization Strategy von Han, Zhizhong, Liu, Zhenbao, Han, Junwei, Vong, Chi-Man, Bu, Shuhui, Chen, C. L. Philip

“… Effective 3-D local features are significant elements for 3-D shape analysis. Existing hand-crafted 3-D local descriptors are effective but usually involve …”
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Myocardium Detection by Deep SSAE Feature and Within-Class Neighborhood Preserved Support Vector Classifier and Regressor von Niu, Yanmin, Qin, Lan, Wang, Xuchu

“… Then it adopts a deep stacked sparse autoencoder (SSAE) network to learn the discriminative deep feature to represent the regions …”
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