Results 11 to 20 of about 1,369,914 (322)
Haptic Feature Extraction [PDF]
Cerebral Cortex, 2005 This study examined the process by which the shape of a haptically explored object is synthesized from the geometric characteristics of simpler constituent elements, such as arcs and ellipses. Subjects traced the outlines of virtual objects by means of whole arm movements.
Weilai Song +2 more
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Deep Private-Feature Extraction [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2020 We present and evaluate Deep Private-Feature Extractor (DPFE), a deep model which is trained and evaluated based on information theoretic constraints. Using the selective exchange of information between a user's device and a service provider, DPFE enables the user to prevent certain sensitive information from being shared with a service provider, while
Seyed Ali Osia +5 more
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A dual quantum image feature extraction method: PSQIFE
IET Image Processing, 2022 In digital image processing, feature extraction occupies a very important position, which is related to the effect of image classification or recognition. At present, effective quantum feature extraction methods are relatively lacking.
Jie Su, Shuhan Lu, Lin Li
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Feature extraction for epileptic seizure detection using machine learning
Current Medicine Research and Practice, 2020 Background: Epilepsy is a common neurological disorder and affects approximately 70 million people worldwide. The traditional approach used by neurologists for the detection of seizure is time consuming.
Renuka Mohan Khati, Rajesh Ingle
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UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples ...
A. Kianisarkaleh +2 more
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Linear feature extraction for ranking [PDF]
Information Retrieval Journal, 2018 We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix.
Gaurav Pandey +4 more
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Face Detection with Effective Feature Extraction [PDF]
, 2010 There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for ...
C. Huang +10 more
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UAT: Universal Attention Transformer for Video Captioning
Sensors, 2022 Video captioning via encoder–decoder structures is a successful sentence generation method. In addition, using various feature extraction networks for extracting multiple features to obtain multiple kinds of visual features in the encoding process is a ...
Heeju Im, Yong-Suk Choi
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Analysis and Evaluation of Feature Selection and Feature Extraction Methods
International Journal of Computational Intelligence Systems, 2023 Hand gestures are widely used in human-to-human and human-to-machine communication. Therefore, hand gesture recognition is a topic of great interest. Hand gesture recognition is closely related to pattern recognition, where overfitting can occur when ...
Rubén E. Nogales, Marco E. Benalcázar
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Relational autoencoder for feature extraction [PDF]
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Feature extraction becomes increasingly important as data grows high dimensional. Autoencoder as a neural network based feature extraction method achieves great success in generating abstract features of high dimensional data. However, it fails to consider the relationships of data samples which may affect experimental results of using original and new
David B. Skillicorn +3 more
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