Results 111 to 120 of about 16,805 (257)

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Creation of a Landslide Susceptibility Map Using Short‐Term Data From the July 2018 Heavy Rainfall in Southern Hiroshima Prefecture

Geological Journal, EarlyView.
This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi, Ting Liu, Toshiro Hata, Rebecca Muenich   +3 more
wiley   +1 more source

A Deep Learning Pipeline for Cell Segmentation and Viability Quantification in 3D Constructs From Fluorescence Microscopy Images

Microscopy Research and Technique, EarlyView.
3D bioprinting requires advanced methods for cell localization and viability assessment. We developed a hybrid and automated pipeline based on the U2‐Net architecture for the analysis of fluorescence microscopy images enabling cell segmentation and viability assessment.
Federica Valtellina, Francesco Iannacci, Bianca Maria Colosimo, Mattia Sponchioni   +3 more
wiley   +1 more source

Deep Learning and Machine Learning Algorithms for Cervical Cancer Segmentation on MRI: A Systematic Review

Journal of Medical Radiation Sciences, EarlyView.
This systematic review summarizes current evidence on machine and deep learning algorithms for MRI‐based cervical cancer segmentation, demonstrating promising diagnostic performance and potential for workflow automation. However, methodological heterogeneity, limited external validation, and low certainty of evidence highlight the need for standardized
Somayeh Haji Ahmadi, Sina Soltan Mohammadi, Abolfazl Koozari, Mohammadreza Elhaie   +3 more
wiley   +1 more source

Robust Spectroscopic Analysis Through Image‐Based Spectral Representation and Deep Learning Techniques

Journal of Raman Spectroscopy, EarlyView.
This study addresses calibration drift in Raman spectroscopy by transforming 1D spectra into 2D spider plot images processed by pretrained convolutional neural networks. This visualization strategy effectively converts detrimental spectral wavenumber shifts into simple image rotations, allowing the deep learning model to maintain high classification ...
Azadeh Mokari, Oleg Ryabchykov, Thomas Bocklitz   +2 more
wiley   +1 more source

From ACR O‐RADS 2022 to Explainable Deep Learning

Journal of Ultrasound in Medicine, EarlyView.
Objectives The 2022 update of the Ovarian‐Adnexal Reporting and Data System (O‐RADS) improves risk stratification of adnexal lesions; however, radiologist interpretation remains subject to inter‐observer variability and conservative diagnostic thresholds.
Ali Abbasian Ardakani, Afshin Mohammadi, Alisa Mohebbi, Anushya Vijayananthan, Sook Sam Leong, Yi Ting Lim, Mohd Kamil Bin Mohamad Fabell, Gernot Hudelist, Balint Balogh, Marlina Tanty Ramli Hamid, U Rajendra Acharya, Sepideh Hatamikia   +11 more
wiley   +1 more source

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

An Improved Mask R-CNN Micro-Crack Detection Model for the Surface of Metal Structural Parts. [PDF]

Sensors (Basel), 2023
Yang F, Huo J, Cheng Z, Chen H, Shi Y.
europepmc   +1 more source

From Planar to 3D Nanophotonic Lenses: Advancing Design, Fabrication, and Applications

Laser &Photonics Reviews, EarlyView.
Three‐dimensional nanophotonic lenses are enabled by an integrated workflow that links design parameterization, full‐wave electromagnetic simulation, computational optimization, and freeform fabrication. This Review summarizes how these tools expand optical design freedom beyond a single patterned plane by enriching the local meta‐atom response and ...
Wei Zhu, Lyudmila V. Goncharova, Eric Johlin   +2 more
wiley   +1 more source

Mask R-CNN-based carotid plaque localization in ultrasound images. [PDF]

J Med Imaging (Bellingham)
Kiernan MJ, Mukaddim RA, Mitchell CC, Maybock J, Wilbrand SM, Dempsey RJ, Varghese T.   +6 more
europepmc   +1 more source