Results 91 to 100 of about 8,989,075 (297)
Tuned Support Vector Machine Classifier for Pedestrian Recognition in Urban Traffic
Ingeniería, 2012 The need for autonomy and intelligent decision-making in automobile flow is booming. For this purpose there are a number of interesting problems related to recognition of features in urban environments. One of the main relevant aspects in this subject is
Henry A Roncancio +3 more
doaj
Advanced Functional Materials, EarlyView.Rapid thermal annealing reconstructs the BCFO/Nb:STO interface into an atomically thin reconstructed interfacial layer, which reshapes the tunneling barrier and converts a high‐TER ferroelectric tunnel junction into an intrinsically nonlinear, self‐rectifying device.
Hojin Lee +21 more
wiley +1 more source
Higher Order Support Vector Random Fields for Hyperspectral Image Classification
ISPRS International Journal of Geo-Information, 2018 This paper addresses the problem of contextual hyperspectral image (HSI) classification. A novel conditional random fields (CRFs) model, known as higher order support vector random fields (HSVRFs), is proposed for HSI classification.
Junli Yang +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A geometry‐reconfigured additive manufacturing strategy converts planar printed soft materials into soft compact neural probes with integrated hydrogel electrodes and microfluidic channels. The resulting NeuroMAP platform enables scalable multichannel recording, localized chemical delivery, stable in vivo electrophysiological recording, and reduced ...
Hyunjin Lee +15 more
wiley +1 more source
Benchmarking least squares support vector machine classifiers. [PDF]
In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a ( convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function
Suykens, Johan +7 more
core
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 +9 more
wiley +1 more source
Optical Detection of Cellular Signals at Material Interfaces
Advanced Healthcare Materials, EarlyView.Emerging functional materials are transforming optical detection of cellular signals. This review highlights optical techniques that exploit the unique optical properties of diverse materials to detect and quantify cellular electrical, chemical, and mechanical signals, and discusses key opportunities and challenges.
Xuchen Ren +5 more
wiley +1 more source
Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier. [PDF]
Transl Lung Cancer Res, 2023 Shen Y +6 more
europepmc +1 more source
Advanced Materials, EarlyView.Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
COVID-19 cluster identification and support vector machine classifier model construction using global healthcare and socio-economic features. [PDF]
Epidemiol Infect, 2023 Guha SK, Sadhukhan S, Niyogi S.
europepmc +1 more source