Results 181 to 190 of about 113,531 (269)

Feature Selection and Hyperparameter Optimization for Machine Learned Classification of 3D Single-Particle Tracking. [PDF]

Chem Biomed Imaging
Chatterjee J, Chatterjee S, Gillett E, Kovalenko N, Fan D, Landes CF.   +5 more
europepmc   +1 more source

Identification of the ubiquitin-proteasome pathway domain by hyperparameter optimization based on a 2D convolutional neural network. [PDF]

Front Genet, 2022
Sikander R, Arif M, Ghulam A, Worachartcheewan A, Thafar MA, Habib S.   +5 more
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Hyperparameter optimization of XGBoost and hybrid CnnSVM for cyber threat detection using modified Harris hawks algorithm. [PDF]

PeerJ Comput Sci
Elwahsh H, Bakhiet A, Khalifa T, Hoxha J, Alsabaan M, Ibrahem MI, Elwahsh M, El-Shafeiy E.   +7 more
europepmc   +1 more source

Nonlinear Hyperparameter Optimization of a Neural Network in Image Processing for Micromachines. [PDF]

Micromachines (Basel), 2021
Shen M, Yang J, Li S, Zhang A, Bai Q.
europepmc   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Integrated Hyperparameter Optimization with Dimensionality Reduction and Clustering for Radiomics: A Bootstrapped Approach. [PDF]

Multimodal Technol Interact
Pawan SJ, Muellner M, Lei X, Desai M, Varghese B, Duddalwar V, Cen SY.   +6 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Image steganalysis using active learning and hyperparameter optimization. [PDF]

Sci Rep
Bohang L, Li N, Yang J, Alfarraj O, Albelhai F, Tolba A, Shaikh ZA, Alizadehsani R, Pławiak P, Yee PL.   +9 more
europepmc   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source