Results 171 to 180 of about 4,317,504 (301)

A Two-Stage Contrastive Learning Framework Grounded in Label-Specific Features for Low-Frequency Labels in Chest X-Ray Multi-Label Classification. [PDF]

Bioengineering (Basel)
Tang S, Huang M, Feng Q.
europepmc   +1 more source

Multi-label classification and features investigation of antimicrobial peptides with various functional classes. [PDF]

iScience, 2023
Chung CR, Liou JT, Wu LC, Horng JT, Lee TY.   +4 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

A weighted difference loss approach for enhancing multi-label classification. [PDF]

Sci Rep
Hu Q, Azrifah Azmi Murad M, Azman AB, Nasharuddin NA.   +3 more
europepmc   +1 more source

Multi-Label Classification in Anime Illustrations Based on Hierarchical Attribute Relationships. [PDF]

Sensors (Basel), 2023
Lan Z, Maeda K, Ogawa T, Haseyama M.
europepmc   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Graph neural network-based multi-label classification of breast cancer using multiparametric MRI and clinical features. [PDF]

Discov Oncol
Salehzehi S, Jafarpoor Nesheli S, Eftekhar A, Shojaee Rocky M, Vejdani Noghreiyan V, Bazazpour A, Arefi ZH, Rezaeijo SM.   +7 more
europepmc   +1 more source

HOMLC-Hyperparameter Optimization for Multi-Label Classification of Intrusion Detection Data for Internet of Things Network. [PDF]

Sensors (Basel), 2023
Sharma A, Rani S, Sah DK, Khan Z, Boulila W.   +4 more
europepmc   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

The design of copper flotation process based on multi-label classification and regression. [PDF]

Sci Rep
Dong H, Wang F, He D, Liu Y.
europepmc   +1 more source