Results 181 to 190 of about 683,409 (316)
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 +5 more
wiley +1 more source
In Search of the Performance- and Energy-Efficient CNN Accelerators
Stanislav G. Sedukhin +2 more
openalex +2 more sources
opXRD: Open Experimental Powder X‐Ray Diffraction Database
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek +23 more
wiley +1 more source
A Fault Identification Method for Micro-Motors Using an Optimized CNN-Based JMD-GRM Approach. [PDF]
Bai Y, Gu Z, Yu J, Chen J.
europepmc +1 more source
Empirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction Modelling [PDF]
Steven Matthew +7 more
openalex +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Sustainable design of organic solar cells utilized machine and deep learning. [PDF]
Mohyeldien OM +2 more
europepmc +1 more source
Peran Citizen Journalism Dalam Pemberitaan Bencana Palu Di Cnn Indonesia
Ahmad Abdiyansyah +1 more
openalex +2 more sources
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki +3 more
wiley +1 more source

