Results 191 to 200 of about 1,480,093 (371)

Detection of potato diseases using image segmentation and multiclass support vector machine

Canadian Conference on Electrical and Computer Engineering, 2017
Monzurul Islam, A. Dinh, K. Wahid, P. Bhowmik   +3 more
semanticscholar   +1 more source

AI‐Assisted Design and Evaluation of SLM‐Ti64 Implants for Enhanced Bone Regeneration

Advanced Healthcare Materials, EarlyView.
AI‐driven simulations of biological healing, combining biomechanical modeling and machine learning, enable personalized orthopedic treatments. By decoding healing patterns influenced by implants and patient‐specific factors, this approach advances fracture repair understanding, optimizes implant design, and supports precision medicine and sustainable ...
Muhammad Usama Zaheer, Muhammad Hassan Razzaq, Mehmet Fatih Aycan, Yogendra Kumar Mishra   +3 more
wiley   +1 more source

Support Vector Machine Based Classification Model for Screening Plasmodium falciparum Proliferation Inhibitors and Non-Inhibitors

Biomedical Engineering and Computational Biology, 2011
Sangeetha Subramaniam, Monica Mehrotra, Dinesh Gupta   +2 more
doaj  

Entanglement detection with quantum support vector machine (QSVM) on near-term quantum devices. [PDF]

Sci Rep
Mahdian M, Mousavi Z.
europepmc   +1 more source

RSVM: Reduced Support Vector Machines

, 2001
Yuh‐Jye Lee, O. L. Mangasarian
openalex   +1 more source

A New Family of Ternary Intermetallic Compounds with Dualistic Atomic Ordering – The ZIP Phases

Advanced Materials, EarlyView.
The ZIP phases are ternary intermetallic compounds with dualistic atomic ordering, i.e., they exhibit one face‐centered cubic (fcc; space group Fd3¯$\bar 3$m) variant and one hexagonal (space group P63/mmc) variant. The ZIP phases in the Nb‐Si‐Ni system are the Nb3SiNi2 (fcc) and Ni3SiNb2 (hexagonal) ternary IMCs, crystal structure schematics of which ...
Matheus A. Tunes, Sean M. Drewry, Franziska Schmidt, James A. Valdez, Matthew M. Schneider, Caitlin A. Kohnert, Tarik A. Saleh, Saryu Fensin, Stuart A. Maloy, Cláudio G. Schön, Sylvain Dubois, Omri Tabo, Anna Eyal, Amit Keren, Asaf Pesach, Ganesh K. Nayak, Stavros‐Richard G. Christopoulos, Marco Molinari, Marcus Hans, Nick Goossens, Shuigen Huang, Jochen M. Schneider, Per O. Å. Persson, Jozef Vleugels, Konstantina Lambrinou   +24 more
wiley   +1 more source

An optimized support vector machine for lung cancer classification system. [PDF]

Front Oncol
Oyediran MO, Ojo OS, Raji IA, Adeniyi AE, Aroba OJ.   +4 more
europepmc   +1 more source

Multifunctional Neural Probes Enable Bidirectional Electrical, Optical, and Chemical Recording and Stimulation In Vivo

Advanced Materials, EarlyView.
Convergence drawing is used to create flexible, microscale, multifunctional fiber‐based neural probes. Optimized materials selection enables individual devices to perform neural recording, electrical stimulation, optogenetics, fiber photometry, fluid delivery, and voltammetric neurotransmitter detection in rodents.
Nicolette Driscoll, Marc‐Joseph Antonini, Taylor M. Cannon, Pema Maretich, Greatness Olaitan, Valerie Doan Phi Van, Keisuke Nagao, Atharva Sahasrabudhe, Emmanuel Vargas Paniagua, Ethan J. Frey, Ye Ji Kim, Sydney Hunt, Melissa Hummel, Sanju Mupparaju, Alan Jasanoff, B. Jill Venton, Polina Anikeeva   +16 more
wiley   +1 more source

α-decay half-life predictions with support vector machine. [PDF]

Sci Rep
Jalili A, Pan F, Draayer JP, Chen AX, Ren Z.   +4 more
europepmc   +1 more source

Synthetic Aspects and Characterization Needs in MOF Chemistry – from Discovery to Applications

Advanced Materials, EarlyView.
Overcoming the challenges of phase discovery, synthesis optimization and scale‐up, characterization, and computational studies is essential to accelerate the large‐scale application of MOFs. Life‐cycle analyses and techno‐economic analyses need to be performed to realistically assess their potential for industrial relevance.
Bastian Achenbach, Aysu Yurdusen, Norbert Stock, Guillaume Maurin, Christian Serre   +4 more
wiley   +1 more source