Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening

J Li, L Pan, M Suvarna, X Wang - Chemical Engineering Journal, 2021 - Elsevier
Hydrogen production from wet organic wastes through supercritical water gasification
(SCWG) promotes sustainable development. However, it is always time-consuming and …

Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource

J Li, X Zhu, Y Li, YW Tong, YS Ok, X Wang - Journal of Cleaner Production, 2021 - Elsevier
Hydrothermal carbonization (HTC) is a promising technology for valuable resources
recovery from high-moisture wastes without pre-drying, while optimization of operational …

Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning

J Li, L Pan, M Suvarna, YW Tong, X Wang - Applied Energy, 2020 - Elsevier
Conversion of wet organic wastes into renewable energy is a promising way to substitute
fossil fuels and avoid environmental deterioration. Hydrothermal carbonization and pyrolysis …

Adversarial stain transfer for histopathology image analysis

A BenTaieb, G Hamarneh - IEEE transactions on medical …, 2017 - ieeexplore.ieee.org
It is generally recognized that color information is central to the automatic and visual
analysis of histopathology tissue slides. In practice, pathologists rely on color, which reflects …

Triplanar ensemble of 3D-to-2D CNNs with label-uncertainty for brain tumor segmentation

R McKinley, M Rebsamen, R Meier, R Wiest - … : Glioma, Multiple Sclerosis …, 2020 - Springer
We introduce a modification of our previous 3D-to-2D fully convolutional architecture,
DeepSCAN, replacing batch normalization with instance normalization, and adding a …

Predicting pedestrian crossing intention in autonomous vehicles: A review

FG Landry, MA Akhloufi - Neurocomputing, 2024 - Elsevier
Road traffic accidents involving collisions between vehicles and pedestrians are a major
cause of death and injury globally. With recent technological progress in the field of …

Classification of aluminum scrap by laser induced breakdown spectroscopy (LIBS) and RGB+ D image fusion using deep learning approaches

D Díaz-Romero, S Van den Eynde, I Zaplana… - Resources …, 2023 - Elsevier
Integrating multi-sensor systems to sort and monitor complex waste streams is one of the
most recent innovations in the recycling industry. The complementary strengths of Laser …

Deep learning regression for quantitative LIBS analysis

S Van den Eynde, DJ Díaz-Romero, I Zaplana… - … Acta Part B: Atomic …, 2023 - Elsevier
One of the most promising innovation strategies for sorting and recycling post-consumer
aluminium scrap is using quantitative Laser-Induced Breakdown Spectroscopy (LIBS) …

Kidney level lupus nephritis classification using uncertainty guided Bayesian convolutional neural networks

PA Cicalese, A Mobiny, Z Shahmoradi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The kidney biopsy based diagnosis of Lupus Nephritis (LN) is characterized by low inter-
observer agreement, with misdiagnosis being associated with increased patient morbidity …

Histological image classification using deep features and transfer learning

S Alinsaif, J Lang - 2020 17th Conference on Computer and …, 2020 - ieeexplore.ieee.org
A major challenge in the automatic classification of histopathological images is the limited
amount of data available. Supervised learning techniques cannot be applied without some …