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Jisuanji Xuebao/Chinese Journal of Computers, ISSN 0254-4164, 06/2017, Volume 40, Issue 6, pp. 1229 - 1251
Journal Article
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), ISSN 1063-6919, 06/2015, Volume 7-12-, pp. 806 - 814
Deep neural networks have achieved remarkable performance in both image classification and object detection problems, at the cost of a large number of... 
Convolutional codes | Accuracy | Neural networks | Redundancy | Sparse matrices | Matrix decomposition | Kernel | Computer vision | Algorithms | Cascades | Mathematical models | Central processing units | Pattern recognition
Conference Proceeding
Neural Networks, ISSN 0893-6080, 08/2019, Volume 116, pp. 279 - 287
Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference... 
Deep learning | Pattern recognition | Convolutional neural networks | Convolution techniques | Machine learning | Image classification | NEUROSCIENCES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms | Neural networks | Analysis
Journal Article
Neurocomputing, ISSN 0925-2312, 04/2017, Volume 234, pp. 11 - 26
Journal Article
Pattern Recognition, ISSN 0031-3203, 05/2018, Volume 77, pp. 354 - 377
In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural... 
Deep learning | Convolutional neural network | RECOGNITION | IMAGES | CLASSIFICATION | TERM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | VISUAL TRACKING | FEATURES | CNNS | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer science | Language processing | Computational linguistics | Machine vision | Neural networks | Natural language interfaces
Journal Article
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), ISSN 2329-9290, 10/2014, Volume 22, Issue 10, pp. 1533 - 1545
Journal Article
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, ISSN 1063-6919, 12/2018, pp. 7794 - 7803
Conference Proceeding
Journal of Sound and Vibration, ISSN 0022-460X, 09/2016, Volume 377, pp. 331 - 345
Vibration analysis is a well-established technique for condition monitoring of rotating machines as the vibration patterns differ depending on the fault or... 
Condition monitoring | Feature learning | Fault detection | Convolutional neural network | Machine learning | Vibration analysis | ACOUSTICS | DIAGNOSIS | MECHANICS | ENGINEERING, MECHANICAL | Magneto-electric machines | Neural networks | Machinery | Analysis | Detectors
Journal Article
Remote Sensing, ISSN 2072-4292, 07/2016, Volume 8, Issue 7, p. 594
A new pansharpening method is proposed, based on convolutional neural networks. We adapt a simple and effective three-layer architecture recently proposed for... 
Super-resolution | Segmentation | Convolutional neural networks | Multiresolution | Enhancement | Machine learning | DATA-FUSION | QUALITY | super-resolution | SPECTRAL RESOLUTION IMAGES | enhancement | machine learning | PAN-SHARPENING METHOD | REMOTE SENSING | multiresolution | segmentation | CONTRAST | convolutional neural networks | LANDSAT THEMATIC MAPPER
Journal Article
05/2017, Volume 60, Issue 6, 7
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000... 
COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | COMPUTER SCIENCE, THEORY & METHODS | Convolutional codes | Control | Usage | Image processing | Neural networks | Methods
Magazine Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 07/2018, Volume 27, Issue 7, pp. 3657 - 3670
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 06/2016, Volume 25, Issue 6, pp. 2529 - 2541
Journal Article
Neurocomputing, ISSN 0925-2312, 01/2017, Volume 219, pp. 88 - 98
As a powerful visual model, convolutional neural networks (CNNs) have demonstrated remarkable performance in various visual recognition problems, and attracted... 
Deep learning | Convolutional neural networks | Hyperspectral image classification | BAND SELECTION | FOREWORD | REPRESENTATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | SPECIAL-ISSUE | Computer science | Neural networks | Analysis
Journal Article
Information Fusion, ISSN 1566-2535, 07/2017, Volume 36, pp. 191 - 207
As is well known, activity level measurement and fusion rule are two crucial factors in image fusion. For most existing fusion methods, either in spatial... 
Deep learning | Multi-focus image fusion | Convolutional neural networks | Fusion rule | Activity level measurement | Image fusion | PERFORMANCE | INFORMATION | COMPUTER SCIENCE, THEORY & METHODS | SIMILARITY | QUALITY ASSESSMENT | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Neural networks | Biomedical engineering | Analysis
Journal Article