Results 181 to 190 of about 60,338 (274)

Emerging Machine Learning Strategies for Digital Processing and Additive Manufacturing of Advanced Ceramics

International Journal of Applied Ceramic Technology, Volume 23, Issue 3, June 2026.
ABSTRACT Machine learning (ML) techniques are increasingly being applied to the development and processing of advanced ceramics, enabling predictive design, formulation optimization, and improved control of manufacturing workflows. This review presents an integrated and application‐oriented analysis of ML approaches in ceramic engineering, with ...
Sioney Teixeira Monteiro, Isaac A. T. Monteiro, J. R. Fernandez‐Gamboa, Yurimiler Leyet Ruiz   +3 more
wiley   +1 more source

Dynamic background motion object semantic segmentation algorithm based on generative adversarial network and transformer collaboration. [PDF]

Sci Rep
Li Y, Luo Z, Chen T, Huang X, Zhong C, Zhu G, Jin D, Cheng C, Zhang Y, Zhao J, Gao P.   +10 more
europepmc   +1 more source

A Comprehensive Review of Traditional and Machine Learning‐Assisted Diffuse Optical Spectroscopy and Imaging Techniques for Dermatological Applications

Advanced Photonics Research, Volume 7, Issue 5, May 2026.
This review critically examines clinical studies on both conventional and machine learning (ML)‐integrated diffuse optical spectroscopy and imaging methods for dermatological applications, with a primary focus on the past decade and inclusion of earlier foundational work where appropriate.
Iftak Hussain, Li Xiuting, Randall Ang Jie, Keertana Vinod Ram, Mark Teo Ju Teng, Valerie Xinhui Teo, Malini Olivo, U. S. Dinish   +7 more
wiley   +1 more source

Keeping up with the regions: a hybrid machine learning framework for estimating regional input-output tables. [PDF]

Sci Rep
De Pretis F, Tortoli D, Caria S.
europepmc   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, Volume 89, Issue 5, Page 791-814, May 2026.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

Research on turbulence-removal optical imaging based on multi-scale GAN and sequential images. [PDF]

Sci Rep
Lu Y, Li Z, Qi D, Zhou L.
europepmc   +1 more source

RNA Modifications: Current Understandings and Future Perspectives

MedComm, Volume 7, Issue 5, May 2026.
Types of RNA modification. We have summarized the currently common types of RNA modifications, including ac4C, m6A, m1A, m5C, m3C, m7G, and ψ, and visually characterized their features through structural formulas. The characteristic structures are marked with a background color different from the background color.
Shiyu Xiao, Tingwen Xiang, Chuan Yang, Xiaohua Wang, Gang Huang, Fei Luo, Zhao Xie, Yueqi Chen   +7 more
wiley   +1 more source

Generative Adversarial Networks for Modeling Bio-Electric Fields in Medicine: A Review of EEG, ECG, EMG, and EOG Applications. [PDF]

Bioengineering (Basel)
Liang J, Zhou Y, Ma K, Jia Y, Zhang Y, Han B, Xiang M.   +6 more
europepmc   +1 more source

Cross‐Site Generalization of CNN‐Based B1+$$ {B}_1^{+} $$ Mapping in UHF MRI

NMR in Biomedicine, Volume 39, Issue 5, May 2026.
The study demonstrates that CNN%‐based B1+$$ {B}_1^{+} $$ mapping transfers across sites with only moderate accuracy loss: while on‐site RMSEs were as low as ~3%, cross‐site predictions increased errors but remained qualitatively robust. Despite these deviations, cross‐site maps successfully enabled dynamic 4kT‐points pulses, achieving flip‐angle ...
Kimon Hadjikiriakos, Felix Krüger, Felix Frederik Zimmermann, Johannes A. Grimm, Constantin Schorling, Max Lutz, Simon Schmidt, Layla Tabea Riemann, Katja Degenhardt, Tobias Schäffter, Mark E. Ladd, Gregory J. Metzger, Christoph Stefan Aigner, Sebastian Schmitter   +13 more
wiley   +1 more source

Dose Prediction Deep Learning-Based Model for VMAT of Prostate Cancer Applying Magnetic Resonance Image (MRI) in Versa HD Linear Accelerator. [PDF]

Adv Biomed Res
Taheri H, Tavakoli M, Mousavi K, Taheri H, Lenjani SL, Farghadani M.   +5 more
europepmc   +1 more source