Results 71 to 80 of about 3,745,728 (280)

Real-valued feature selection for process approximation and prediction [PDF]

, 2009
The selection of features for classification, clustering and approximation is an important task in pattern recognition, data mining and soft computing. For real-valued features, this contribution shows how feature selection for a high number of features ...
Heister, Frank, Brause, Rüdiger
core  

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Unsupervised feature selection based on generalized regression model with linear discriminant constraints

Complex & Intelligent Systems
Unsupervised feature selection (UFS) methods play a crucial role in improving the efficiency of extracting relevant information and reducing computational complexity in the context of big data analysis.
Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai   +6 more
doaj   +1 more source

Self‐Cleaning Sensor Surfaces for Long‐Term Environmental Monitoring

Advanced Engineering Materials, EarlyView.
Long‐term use of unattended outdoor sensors without soiling or biofouling is achieved through generation of a micro‐ and nanorough cuvette surface by combing hydrophobic nanoparticles with fluorinated polymers, crosslinked and surface‐attached through CHic chemistry. The coating demonstrates self‐cleaning behavior and prolonged outdoor stability, which
Sanam Kumari Rajak, Yasmina Frey, Ulrike Wallrabe, Oswald Prucker, Jürgen Rühe   +4 more
wiley   +1 more source

How PCA helps multi-criteria decision making for feature selection: A feature fusion approach in bioinformatics and gene expression data

Alexandria Engineering Journal
In high-dimensional data analysis, unsupervised feature selection plays a crucial role in enhancing model interpretability and reducing computational cost. While Principal Component Analysis (PCA) and Multi-Criteria Decision-Making (MCDM) methods such as
Mohsen Habibollahi, Amin Hashemi, Mohammad Bagher Dowlatshahi, Marjan Kuchaki Rafsanjani, Varsha Arya, Brij B. Gupta   +5 more
doaj   +1 more source

Printed Integrated Logic Circuits Based on Chitosan‐Gated Organic Transistors for Future Edible Systems

Advanced Functional Materials, EarlyView.
Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco, Valerio Francesco Annese, Valerio Galli, Ilaria Penna, Debora Russo, Marina Veronesi, Rita Scarpelli, Stefania Sabella, Mario Caironi   +8 more
wiley   +1 more source

UDSFS: Unsupervised deep sparse feature selection

, 2016
In this paper, we focus on unsupervised feature selection. As we have known, the combination of several feature units into a whole feature vector is broadly adopted for effective object representation, which may inevitably includes some irrelevant ...
Fan BJ(范保杰), Yu HB(于海斌), Yang YS(杨云生), Cong Y(丛杨), Wang S(王帅)   +4 more
core  

Gait feature subset selection by mutual information [PDF]

, 2007
Feature selection is an important pre-processing step for pattern recognition. It can discard irrelevant and redundant information that may not only affect a classifier’s performance, but also tell against system’s efficiency.
Mark S. Nixon, M.S. Nixon, Nixon, Mark, Mark. S. Nixon, Baofeng Guo, Guo, Baofeng   +5 more
core   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Unsupervised Feature Subset Selection [PDF]

, 2003
This master thesis has been developed in the domain of Decision Support Systems and it covers the sparsely researched area of unsupervised feature subset selection for data clustering.
Thomsen, Casper, Søndberg-Madsen, Nicolaj   +1 more
core   +1 more source