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Pattern Recognition, ISSN 0031-3203, 05/2018, Volume 77, pp. 126 - 139
•Showing that combining original data with a proper nonlinear embedding could be a better basis for adaptive graph learning.•Development of dual... 
Graph Laplacian | Embedding | Extreme learning machine | Graph-based clustering | Constrained Laplacian rank | MACHINE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Rankings | Algorithms | Neural networks | Analysis | Methods
Journal Article
Neurocomputing, ISSN 0925-2312, 02/2018, Volume 277, pp. 78 - 88
Clustering generic data, i.e., data not specific to a particular field, is a challenging problem due to their diverse complex structures in the original... 
Feature learning | k-means | Embedding | Extreme learning machine | Clustering | Manifold regularization | FRAMEWORK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
IEEE Intelligent Systems, ISSN 1541-1672, 11/2013, Volume 28, Issue 6, pp. 30 - 59
Journal Article
Procedia Computer Science, ISSN 1877-0509, 2015, Volume 53, Issue 1, pp. 391 - 399
Generic object recognition is to classify the object to a generic category. Intra-class variabilities cause big troubles for this task. Traditional methods... 
local receptive fields | Generic object recognition | Extreme Learning Machine (ELM) | Local receptive fields
Journal Article
IEEE transactions on industrial electronics (1982), ISSN 1557-9948, 2020, Volume 67, Issue 3, pp. 2360 - 2370
Journal Article
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 10/2017, Volume 2018-, pp. 1015 - 1022
Feature representation/learning is an essential step for many computer vision tasks (like image classification) and is broadly categorized as 1) deep feature... 
Support vector machines | Computer vision | Feature extraction | Convolution | Noise measurement | Principal component analysis
Conference Proceeding
2017 IEEE International Conference on Image Processing (ICIP), ISSN 1522-4880, 09/2017, Volume 2017-, pp. 1297 - 1301
Conference Proceeding
2011 IEEE 15th International Symposium on Consumer Electronics (ISCE), ISSN 0747-668X, 06/2011, pp. 272 - 277
This paper tackles the problem of detecting the swinging action of an electronic handbell. It describes a threshold-based algorithm that is able to detect an... 
Accelerometers | Accuracy | Noise | Hidden Markov models | Gesture recognition | Acceleration | Equations
Conference Proceeding
Magazine Article
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