Results 141 to 150 of about 427,183 (276)

PET-TURTLE: Deep Unsupervised Support Vector Machines for Imbalanced Data Clusters. [PDF]

IEEE Signal Process Lett
Salazar Cavazos J.
europepmc   +1 more source

SVM-DO: identification of tumor-discriminating mRNA signatures via support vector machines supported by Disease Ontology. [PDF]

Turk J Biol, 2023
Özer ME, Özbek Sarica P, Arğa KY.
europepmc   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

Driver Fatigue Detection using EEG Microstate Features and Support Vector Machines. [PDF]

J Biomed Phys Eng
Yaddasht Z, Kazemi K, Danyali H, Aarabi A.   +3 more
europepmc   +1 more source

Universal expressiveness of variational quantum classifiers and quantum kernels for support vector machines. [PDF]

Nat Commun, 2023
Jäger J, Krems RV.
europepmc   +1 more source

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

Advanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee, Moon‐Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son, Munwon Lim, Minho Kang, Dong Yun Lee, Donghyun Lim, Jung‐Hoon Park, Gi Doo Cha, Soo‐Hong Lee, Tae‐Sik Jang, Kisuk Yang, Yunho Jeong, Youngho Eom, Hyun‐Do Jung   +21 more
wiley   +1 more source

A hybrid stacked autoencoder and support vector machines-based expert system for heart failure detection. [PDF]

Sci Rep
Kamal MM, Khan W, Shambour QY, Gafar MA, Alarifi A, Sheraz M, Chuah TC.   +6 more
europepmc   +1 more source

Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction. [PDF]

MethodsX, 2023
Svane J, Wiktorski T, Ørn S, Eftestøl TC.   +3 more
europepmc   +1 more source

Superior Impact‐Resistant Composite Hydrogels Through an Ionic Coupling Strategy

Advanced Materials, EarlyView.
An ionic coupling strategy is developed to simultaneously reinforce networks and interfaces in composite hydrogels. Sodium citrate acts as a single multifunctional ionic coupler to strengthen the poly(vinyl alcohol) matrix via the Hofmeister effect, reinforce the chitosan–sodium alginate nanofiber network via desolvation and electrostatic crosslinking,
Hao Zhuo, Quyang Liu, Xinyu Dong, Hongzhi Zheng, Lingyi Hong, Wei Zhai   +5 more
wiley   +1 more source

Support Vector Machines

, 2003
In this report we present an introductory overview of Support Vector Machines (SVMs). SVMs are supervised learning machines that can be analysed theoretically using concepts from computational learning theory while being able to achieve good performance when applied to real-world problems.
Schölkopf, B., Smola, A.
openaire   +3 more sources