Results 41 to 50 of about 3,899,370 (385)
Coloring Local Feature Extraction [PDF]
, 2006 Although color is commonly experienced as an indispensable quality in describing the world around us, state-of-the art local feature-based representations are mostly based on shape description, and ignore color information. The description of color is hampered by the large amount of variations which causes the measured color values to vary ...
van de Weijer, Joost, Schmid, Cordelia
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Multi-Label Feature Extraction Method Relied on Feature-Label Dependence Auto-encoder
Jisuanji kexue yu tansuo, 2020 In multi-label learning, how to deal with high-dimensional features has always been one of the research difficulties. The feature extraction algorithm can effectively solve the problem of classification performance degra-dation caused by high ...
CHENG Yusheng, LI Zhiwei, PANG Shufang
doaj +1 more source
Style Feature Extraction Using Contrastive Conditioned Variational Autoencoders with Mutual Information Constraints [PDF]
, 2023 Extracting fine-grained features such as styles from unlabeled data is crucial for data analysis. Unsupervised methods such as variational autoencoders (VAEs) can extract styles that are usually mixed with other features. Conditional VAEs (CVAEs) can isolate styles using class labels; however, there are no established methods to extract only styles ...
arxiv +1 more source
Spatio-temporal Gait Feature with Global Distance Alignment [PDF]
arXiv, 2022 Gait recognition is an important recognition technology, because gait is not easy to camouflage and does not need cooperation to recognize subjects. However, many existing methods are inadequate in preserving both temporal information and fine-grained information, thus reducing its discrimination.
arxiv
Transport Model for Feature Extraction
SIAM Journal on Mathematics of Data Science, 2021 We present a new feature extraction method for complex and large datasets, based on the concept of transport operators on graphs. The proposed approach generalizes and extends the many existing data representation methodologies built upon diffusion processes, to a new domain where dynamical systems play a key role.
Wojciech Czaja +3 more
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Journal of Big DataInternet of Things (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine learning approaches have been developed for network intrusion detection in IoT.
Jing Li +3 more
semanticscholar +1 more source
Feature Extraction Methods: A Review
Journal of Physics: Conference Series, 2020 Feature extraction is the main core in diagnosis, classification, clustering, recognition, and detection. Many researchers may by interesting in choosing suitable features that used in the applications.
Wamidh K. Mutlag +3 more
semanticscholar +1 more source
Ilkom Jurnal Ilmiah, 2022 This study aims to build a system to identify the ripeness level of chayote that can be done easily and without damaging the quality of the chayote.
Siska Anraeni +2 more
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Jurnal Ilmiah SINERGI, 2020 This research discusses the detection of embryonic eggs using the k-means clustering method based on statistical feature extraction. The processes that occur in detection are image acquisition, image enhancement, feature extraction, and identification ...
Shoffan Saifullah
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Extraction of Projection Profile, Run-Histogram and Entropy Features Straight from Run-Length Compressed Text-Documents [PDF]
2013 Second IAPR Asian Conference on Pattern Recognition, Pages
813-817, 2014 Document Image Analysis, like any Digital Image Analysis requires identification and extraction of proper features, which are generally extracted from uncompressed images, though in reality images are made available in compressed form for the reasons such as transmission and storage efficiency.
arxiv +1 more source