Results 81 to 90 of about 4,627,276 (412)
Application of multiobjective genetic programming to the design of robot failure recognition systems [PDF]
, 2009 We present an evolutionary approach using multiobjective genetic programming (MOGP) to derive optimal feature extraction preprocessing stages for robot failure detection.
Rockett, P.I., Zhang, Y.
core +1 more source
FoxO1 signaling in B cell malignancies and its therapeutic targeting
FEBS Letters, EarlyView.FoxO1 has context‐specific tumor suppressor or oncogenic character in myeloid and B cell malignancies. This includes tumor‐promoting properties such as stemness maintenance and DNA damage tolerance in acute leukemias, or regulation of cell proliferation and survival, or migration in mature B cell malignancies.
Krystof Hlavac +3 more
wiley +1 more source
Complexity, 2021 Through the analysis of facial feature extraction technology, this paper designs a lightweight convolutional neural network (LW-CNN). The LW-CNN model adopts a separable convolution structure, which can propose more accurate features with fewer ...
Cheng Di, Jing Peng, Yihua Di, Siwei Wu
doaj +1 more source
Fingerprint Feature Extraction for Indoor Localization
Sensors, 2021 This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area
Jehn-Ruey Jiang +2 more
doaj +1 more source
Modular Autoencoders for Ensemble Feature Extraction [PDF]
, 2015 We introduce the concept of a Modular Autoencoder (MAE), capable of learning a set of diverse but complementary representations from unlabelled data, that can later be used for supervised tasks.
Brown, Gavin, Reeve, Henry W J
core +1 more source
SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2018 As an unsupervised dimensionality reduction method, the principal component analysis (PCA) has been widely considered as an efficient and effective preprocessing step for hyperspectral image (HSI) processing and analysis tasks.
Junjun Jiang +5 more
semanticscholar +1 more source
FEBS Letters, EarlyView.Metabolic dysfunction‐associated steatotic liver disease (MASLD) affects nearly one‐third of the global population and poses a significant risk of progression to cirrhosis or liver cancer. Here, we discuss the roles of hepatic dendritic cell subtypes in MASLD, highlighting their distinct contributions to disease initiation and progression, and their ...
Camilla Klaimi +3 more
wiley +1 more source
Automatic Detection of Facial Midline And Its Contributions To Facial Feature Extraction
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2007 We propose a novel approach for detection of the facial midline from a frontal face image. Using midline as a guide reduces computational cost required for facial feature extraction (FFE) because the midline is capable of restricting multi-dimensional ...
Wataru Ohyama +3 more
doaj +1 more source
COMPARISOM OF WAVELET-BASED AND HHT-BASED FEATURE EXTRACTION METHODS FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Hyperspectral images, which contain rich and fine spectral information, can be used to identify surface objects and improve land use/cover classification accuracy.
X.-M. Huang, P.-H. Hsu
doaj +1 more source
Feature Extraction Framework based on Contrastive Learning with Adaptive Positive and Negative Samples [PDF]
arXiv, 2022 In this study, we propose a feature extraction framework based on contrastive learning with adaptive positive and negative samples (CL-FEFA) that is suitable for unsupervised, supervised, and semi-supervised single-view feature extraction. CL-FEFA constructs adaptively the positive and negative samples from the results of feature extraction, which ...
arxiv