Suchergebnisse - multiscale kernel sparse coding-based classification

Multiscale kernel sparse coding‐based classifier for HRRP radar target recognition.

Autoren: Xiong, Wei Zhang, Gong Liu, Su et al.

Quelle: IET Radar, Sonar & Navigation (Wiley-Blackwell). Dec2016, Vol. 10 Issue 9, p1594-1602. 9p.

Schlagwörter: *IMAGE recognition (Computer vision), *OBJECT recognition (Computer vision), *RADAR targets, *GAUSSIAN processes, *WAVELET transforms

Polarimetric SAR image classification using binary coding‐based polarimetric‐morphological features.

Quelle: IET Image Processing (Wiley-Blackwell); Dec2022, Vol. 16 Issue 14, p3715-3736, 22p

Schlagwörter: BINARY codes, SYNTHETIC aperture radar, HIGH resolution imaging, FEATURE extraction, ORDER statistics, LAND cover

A Novel Multi-Type Image Coding Method Acting on Supervised Hierarchical Deep Spiking Convolutional Neural Networks for Image Classification.

Autoren: Liu, Fang Xu, Jialin Yang, Jie et al.

Quelle: Cognitive Computation; Feb2025, Vol. 17 Issue 1, p1-17, 17p

Compressive feature and kernel sparse coding‐based radar target recognition.

Autoren: Yang, Shuyuan Ma, Yonggang Wang, Min et al.

Quelle: IET Radar, Sonar & Navigation (Wiley-Blackwell); Aug2013, Vol. 7 Issue 7, p755-763, 9p

Schlagwörter: RADAR targets, TARGET acquisition, DATABASES, RECOGNITION (Philosophy), ENCODING

Component adaptive sparse representation for hyperspectral image classification.

Autoren: Bortiew, Amos Patra, Swarnajyoti Bruzzone, Lorenzo

Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Oct2024, Vol. 28 Issue 20, p11911-11925, 15p

Schlagwörter: IMAGE recognition (Computer vision), SPATIAL ability, IMAGE representation, NEIGHBORHOODS, HYPERSPECTRAL imaging systems, PINE, SPECTRAL imaging

Hierarchical sparse Bayesian learning with adaptive Laplacian prior for single image super-resolution.

Autoren: Qi, Mingming Zhou, Yue Hu, Yiwei et al.

Quelle: Scientific Reports; 10/17/2025, Vol. 15 Issue 1, p1-17, 17p

Schlagwörter: HIERARCHICAL Bayes model, HIGH resolution imaging, IMAGE processing, MATHEMATICAL optimization

Incorporation of Histogram Intersection and Semantic Information into Non-Negative Local Laplacian Sparse Coding for Image Classification.

Autoren: Shi, Ying Wan, Yuan Wang, Xinjian et al.

Quelle: Mathematics (2227-7390); Jan2025, Vol. 13 Issue 2, p219, 23p

Schlagwörter: IMAGE recognition (Computer vision), SUPPORT vector machines, ALGORITHMS, HISTOGRAMS, IMAGE representation

TA-MSA: A Fine-Tuning Framework for Few-Shot Remote Sensing Scene Classification.

Autoren: Li, Xiang Sun, Yumei Peng, Xiaoming et al.

Quelle: Remote Sensing; Apr2025, Vol. 17 Issue 8, p1395, 22p

Schlagwörter: REMOTE sensing, CLASSIFICATION, GENERALIZATION

Triple Graph Convolutional Network for Hyperspectral Image Feature Fusion and Classification.

Autoren: Imani, Maryam Cerra, Daniele

Quelle: Remote Sensing; May2025, Vol. 17 Issue 9, p1623, 23p

Schlagwörter: IMAGE recognition (Computer vision), IMAGE fusion, FEATURE extraction, PIXELS, CLASSIFICATION

Multi-Branch Deep Learning Framework for Land Scene Classification in Satellite Imagery.

Autoren: Khan, Sultan Daud Basalamah, Saleh

Quelle: Remote Sensing; Jul2023, Vol. 15 Issue 13, p3408, 25p

Schlagwörter: DEEP learning, REMOTE sensing, URBAN planning, CLASSIFICATION, WORK design, OPTICAL remote sensing, MULTISCALE modeling, REMOTE-sensing images

Firma/Körperschaft: UNIVERSITY of California, Merced

TFI-Fusion: Hierarchical Triple-Stream Feature Interaction Network for Infrared and Visible Image Fusion.

Autoren: Zhao, Mingyang Su, Shaochen Li, Hao

Quelle: Information; Oct2025, Vol. 16 Issue 10, p844, 24p

Schlagwörter: IMAGE fusion, INFRARED imaging, MULTISENSOR data fusion, MATRIX decomposition, PHOTOGRAPHIC imaging software

Transformer-based approaches for neuroimaging: an in-depth review of their role in classification and regression tasks.

Autoren: Zhu, Xinyu Sun, Shen Lin, Lan et al.

Quelle: Reviews in the Neurosciences; Feb2025, Vol. 36 Issue 2, p209-228, 20p

Schlagwörter: TRANSFORMER models, DEEP learning, BRAIN imaging, CLASSIFICATION, EXHIBITIONS

A Comprehensive Survey on Real-Time Image Super-Resolution for IoT and Delay-Sensitive Applications.

Autoren: Rasool, M. J. Aashik Ahmad, Shabir Mardieva, Sevara et al.

Quelle: Applied Sciences (2076-3417); Jan2025, Vol. 15 Issue 1, p274, 26p

Schlagwörter: OBJECT recognition (Computer vision), HIGH resolution imaging, IMAGE intensifiers, IMAGING systems, CLASSIFICATION algorithms

Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification.

Autoren: Qingshan Liu Renlong Hang Huihui Song et al.

Quelle: IEEE Transactions on Geoscience & Remote Sensing; Jan2018, Vol. 56 Issue 1, p117-126, 10p

Schlagwörter: NEURAL circuitry, REMOTE-sensing images, HYPERSPECTRAL imaging systems, IMAGE analysis, MACHINE learning

A REVIEW ON MULTIPLE-FEATURE-BASED ADAPTIVE SPARSE REPRESENTATION (MFASR) AND OTHER CLASSIFICATION TYPES.

Autoren: Srinivasan, S. Rajakumar, K.

Quelle: International Journal on Smart Sensing & Intelligent Systems; Sep2017, Vol. 10 Issue 3, p567-593, 27p

Schlagwörter: SPARSE graphs, SPARSE approximations, HYPERSPECTRAL imaging systems, FEATURE extraction, ASSISTIVE computer technology

A Multiscale Deeply Described Correlations-Based Model for Land-Use Scene Classification.

Autoren: Kunlun Qi Chao Yang Qingfeng Guan et al.

Quelle: Remote Sensing; Sep2017, Vol. 9 Issue 9, p917, 17p

Schlagwörter: LAND use, HIGH resolution imaging, LAND cover, STATISTICAL correlation, ARTIFICIAL neural networks, VECTOR quantization

Scene classification for aerial images based on CNN using sparse coding technique.

Autoren: Qayyum, Abdul Malik, Aamir Saeed Saad, Naufal M et al.

Quelle: International Journal of Remote Sensing; Apr2017, Vol. 38 Issue 8-10, p2662-2685, 24p, 6 Color Photographs, 6 Diagrams, 2 Charts, 5 Graphs

Schlagwörter: AERIAL photogrammetry, DRONE aircraft, REMOTE-sensing images, CONVOLUTION codes, ARTIFICIAL neural networks

Remote sensing image super-resolution using multi-scale convolutional sparse coding network.

Autoren: Cheng, Ruihong Wang, Huajun Luo, Ping

Quelle: PLoS ONE; 10/26/2022, Vol. 17 Issue 10, p1-15, 15p

Schlagwörter: REMOTE sensing, HIGH resolution imaging, LINEAR network coding, CONVOLUTIONAL neural networks, IMAGE reconstruction

Machine Learning and Deep Learning Techniques for Spectral Spatial Classification of Hyperspectral Images: A Comprehensive Survey.

Autoren: Grewal, Reaya Singh Kasana, Singara Kasana, Geeta

Quelle: Electronics (2079-9292); Feb2023, Vol. 12 Issue 3, p488, 34p

Schlagwörter: DEEP learning, MACHINE learning, SUPPORT vector machines, LAND cover

AFDL: a new adaptive fuzzy dictionary learning for medical image classification.

Autoren: Ghasemi, Majid Kelarestaghi, Manoochehr Eshghi, Farshad et al.

Quelle: Pattern Analysis & Applications; 2021, Vol. 24 Issue 1, p145-164, 20p

Schlagwörter: MEDICAL coding