Search Results - stacked sparse autoencoder(ssad)

基于深度堆栈网络的心电信号识别. (Chinese)

Alternate Title: ECG Signal Recognition Based on Deep Stacked Network. (English)

Authors: 张锐 王茹 黄俊 et al.

Source: Journal of Harbin University of Science & Technology; Jun2021, Vol. 26 Issue 3, p108-114, 7p

Subject Terms: PROBLEM solving, ELECTROCARDIOGRAPHY, ALGORITHMS, DATABASES

A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network.

Authors: Qu, Yuanyuan Li, Tao Fu, Shichen et al.

Source: Nonlinear Dynamics; Jan2025, Vol. 113 Issue 1, p459-478, 20p

Research on weld seam feature extraction and defect identification technology.

Authors: Shang, Fei Cai, Dandan Sun, Bo et al.

Source: Nondestructive Testing & Evaluation; Aug2025, Vol. 40 Issue 8, p3339-3376, 38p

Subject Terms: NONDESTRUCTIVE testing, QUALITY control, CONVOLUTIONAL neural networks, WELDED joints, DEEP learning, IMAGE processing, FAULT diagnosis, STRUCTURAL reliability

Deep Embedded Auto-encoder for End-to-End Unsupervised Image Anomaly Detection.

Authors: Huang, Xuan Tang, Hailin

Source: International Journal of Computational Intelligence Systems; 6/2/2025, Vol. 18 Issue 1, p1-22, 22p

Improved autoencoder for unsupervised anomaly detection.

Authors: Cheng, Zhen Wang, Siwei Zhang, Pei et al.

Source: International Journal of Intelligent Systems; Dec2021, Vol. 36 Issue 12, p7103-7125, 23p

Subject Terms: ANOMALY detection (Computer security), INTRUSION detection systems (Computer security), DATA structures, DEEP learning, SAMPLING errors

A novel deep model for image recognition.

Authors: Zhu, Ming Wu, Yan

Source: 2014 IEEE 5th International Conference on Software Engineering & Service Science; 2014, p373-376, 4p

Latent feature reconstruction for unsupervised anomaly detection.

Authors: Lin, Jinghuang He, Yifan Xu, Weixia et al.

Source: Applied Intelligence; Oct2023, Vol. 53 Issue 20, p23628-23640, 13p

Subject Terms: INTRUSION detection systems (Computer security), DEEP learning, MINORITIES

A Survey on the Applications of Semi-supervised Learning to Cyber-security.

Authors: Mvula, Paul Kiyambu Branco, Paula Jourdan, Guy-Vincent et al.

Source: ACM Computing Surveys; Oct2024, Vol. 56 Issue 10, p1-41, 41p

Subject Terms: ARTIFICIAL intelligence, ARTIFICIAL neural networks, REINFORCEMENT learning, DISTRIBUTED artificial intelligence, COMPUTER science conferences, INTRUSION detection systems (Computer security)

Abstract Supplement ACR Convergence 2024.

Source: Arthritis & Rheumatology; Sep2024 Supplement 1, Vol. 76, p1-5598, 5598p

Subject Terms: CONFERENCES & conventions, RHEUMATOLOGY

Geographic Terms: WASHINGTON (D.C.), UNITED States

A Novel Knowledge Distillation Method for Self-Supervised Hyperspectral Image Classification.

Authors: Chi, Qiang Lv, Guohua Zhao, Guixin et al.

Source: Remote Sensing; Sep2022, Vol. 14 Issue 18, pN.PAG-N.PAG, 20p

Subject Terms: MACHINE learning, SUPERVISED learning, JUDGMENT (Psychology), DEEP learning, PROBLEM solving, CLASSIFICATION

Temporal Action Detection Methods Based on Deep Learning.

Authors: Shen, Junyi Li, Ma Zhang, Jikai

Source: International Journal of Pattern Recognition & Artificial Intelligence; Mar2022, Vol. 35 Issue 3, p1-24, 24p

Subject Terms: DEEP learning, TASK analysis, EVALUATION methodology

SDD-CNN: Small Data-Driven Convolution Neural Networks for Subtle Roller Defect Inspection.

Authors: Xu, Xiaohang Zheng, Hong Guo, Zhongyuan et al.

Source: Applied Sciences (2076-3417); Apr2019, Vol. 9 Issue 7, p1364, 16p

Subject Terms: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, MATHEMATICAL convolutions, ROLLER bearings, ROTATING machinery, PIPELINE inspection, SURFACE defects, INSPECTION & review

Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions.

Authors: Leo, Marco Bernava, Giuseppe Massimo Carcagnì, Pierluigi et al.

Source: Sensors (14248220); Feb2022, Vol. 22 Issue 3, p866, 1p

Subject Terms: MOTION analysis, NEUROLOGICAL disorders, MACHINE learning, CENTRAL nervous system, DIAGNOSIS

Artificial Intelligence and Robotics

Authors: Huimin Lu

Resource Type: eBook.

Subjects: Artificial intelligence, Image processing—Digital techniques, Computer vision, Computer engineering, Computer networks

Categories: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Image Processing, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Networking / General, COMPUTERS / Hardware / General

Encyclopedia of Cryptography, Security and Privacy

Authors: Sushil Jajodia Pierangela Samarati Moti Yung

Resource Type: eBook.

Subjects: Data structures (Computer science), Information theory, Cryptography, Data encryption (Computer science), Coding theory

Categories: COMPUTERS / Database Administration & Management, COMPUTERS / Information Theory, COMPUTERS / Security / Cryptography & Encryption

Advanced Intelligent Computing Technology and Applications

Authors: De-Shuang Huang Haiming Chen Bo Li et al.

Resource Type: eBook.

Subjects: Computational intelligence--Congresses

Categories: COMPUTERS / Artificial Intelligence / General

Data Science and Applications

Authors: Satyasai Jagannath Nanda Rajendra Prasad Yadav Amir H. Gandomi et al.

Resource Type: eBook.

Subjects: Data mining--Congresses, Computer science--Congresses, Big data--Congresses, Artificial intelligence--Congresses

Categories: COMPUTERS / Artificial Intelligence / General

Intelligent and Fuzzy Systems

Authors: Cengiz Kahraman Selcuk Cebi Basar Oztaysi et al.

Resource Type: eBook.

Categories: COMPUTERS / Data Science / General

Design Optimization Using Artificial Intelligence

Authors: Satya Ranjan Mishra Apul Narayan Dev Alok Kumar Pandey et al.

Resource Type: eBook.

Subjects: Artificial intelligence--Engineering applications, Artificial intelligence

Categories: TECHNOLOGY & ENGINEERING / Electrical, COMPUTERS / Computer Engineering, TECHNOLOGY & ENGINEERING / Electronics / General

Deep Learning for Video Understanding

Authors: Zuxuan Wu Yu-Gang Jiang

Resource Type: eBook.

Subjects: Telecommunication, Signal processing, Computer vision, Multimedia systems

Categories: TECHNOLOGY & ENGINEERING / Telecommunications, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Interactive & Multimedia, TECHNOLOGY & ENGINEERING / Signals & Signal Processing