Results 51 to 60 of about 14,357 (268)
Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
DEEP NON-NEGATIVE MATRIX FACTORIZATION MODEL FOR CLUSTERING-BASED IMAGE DENOISING [PDF]
Proceedings on Engineering SciencesTechnologies like self-driving cars and cleaning robots are emerging as mainstream technologies. These technologies make use of cognitive recognition.
Shaily Malik +5 more
doaj +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 Auto-encoding is an important task which is typically realized by deep neural networks (DNNs) such as convolutional neural networks (CNN). In this paper, we propose EncoderForest (abbrv. eForest), the first tree ensemble based auto-encoder.
Ji Feng, Zhi-Hua Zhou
openaire +2 more sources
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 +5 more
wiley +1 more source
Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection
IEEE AccessSurveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods.
Asim Niaz +4 more
doaj +1 more source
Polymer Substrates for Flexible Sensors: Advances and Contributions to Smart Agriculture
Advanced Functional Materials, EarlyView.This review comprehensively summarizes recent advances in polymer‐based flexible sensors for smart agriculture, focusing on polymer substrate design, interface engineering, and applications in soil, plant, animal, aquaculture, and post‐harvest monitoring.
Yihui Li +12 more
wiley +1 more source
Enhancing anomaly detection with topology-aware autoencoders
Machine Learning: Science and TechnologyAnomaly detection in high-energy physics is essential for identifying new physics beyond the Standard Model. Autoencoders provide a signal-agnostic approach but are limited by the topology of their latent space.
Vishal S Ngairangbam +3 more
doaj +1 more source
Applied SciencesThis study proposes a deep learning framework for Protein Secondary Structure Prediction (PSSP) that prioritizes computational efficiency while preserving classification accuracy.
Yahya Najib Hamood Al-Shameri +3 more
doaj +1 more source
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source