Results 101 to 110 of about 5,853,511 (292)

Application of Wavelet Packet Entropy Flow Manifold Learning in Bearing Factory Inspection Using the Ultrasonic Technique

Sensors, 2014
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal ...
Xiaoguang Chen, Dan Liu, Guanghua Xu, Kuosheng Jiang, Lin Liang   +4 more
doaj   +1 more source

Neural manifold under plasticity in a goal driven learning behaviour.

PLoS Computational Biology, 2021
Neural activity is often low dimensional and dominated by only a few prominent neural covariation patterns. It has been hypothesised that these covariation patterns could form the building blocks used for fast and flexible motor control.
Barbara Feulner, Claudia Clopath
doaj   +1 more source

Advancing Research on Biomaterials and Biological Materials with Scanning Electron Microscopy under Environmental and Low Vacuum Conditions

Advanced Engineering Materials, EarlyView.
Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel, Lea Dierker, Antoine Eyram Kwame, Kim Nora Wagner, Jonas J. Unterholzner, Jan‐Henning Dirks, Dorothea Brüggemann   +6 more
wiley   +1 more source

Local non‐linear alignment for non‐linear dimensionality reduction

IET Computer Vision, 2017
In manifold learning, alignment is performed with the objective of deriving the global low‐dimensional coordinates of input data from their local coordinates.
Guo Niu, Zhengming Ma
doaj   +1 more source

Learning a Robust Local Manifold Representation for Hyperspectral Dimensionality Reduction

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
Local manifold learning has been successfully applied to hyperspectral dimensionality reduction in order to embed nonlinear and nonconvex manifolds in the data.
Danfeng Hong, Naoto Yokoya, Xiao Xiang Zhu   +2 more
doaj   +1 more source

Joint & Progressive Learning from High-Dimensional Data for Multi-Label Classification [PDF]

, 2018
Despite the fact that nonlinear subspace learning techniques (e.g. manifold learning) have successfully applied to data representation, there is still room for improvement in explainability (explicit mapping), generalization (out-of-samples), and cost ...
Hong, Danfeng, Xu, Jian, Yokoya, Naoto, Zhu, Xiaoxiang   +3 more
core   +1 more source

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Advanced Functional Materials, EarlyView.
Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai, Md Shakhawath Hossain, Nhat Minh Nguyen, Yongliang Chen, Chaohao Chen, Xiaoxue Xu, Quang Thang Trinh, Toan Dinh, Toan Trong Tran   +8 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques

IEEE Access
Manifold learning techniques aim to the non-linear dimension reduction of data. Dimension reduction is the field of interest and demand of many data analysts and is widely used in computer vision, image processing, pattern recognition, neural networks ...
Amna Ashraf, Nazri Mohd Nawi, Muhammad Aamir   +2 more
doaj   +1 more source

Motion-compensated frame rate up-conversion in carotid ultrasound images using optical flow and manifold learning

Türk Kardiyoloji Derneği Arşivi, 2019
Objective: Carotid ultrasonography is a reliable and non-invasive method to evaluate atherosclerosis disease and its complications. B-mode cineloops are widely used to assess the severity of atherosclerosis and its progression; ho- wever, tracking rapid ...
Fereshteh Yousefi Rizi, Sima Navabian, Zahra Alizadeh Sani   +2 more
doaj   +1 more source