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Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening
Hydrogen production from wet organic wastes through supercritical water gasification
(SCWG) promotes sustainable development. However, it is always time-consuming and …
(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
Hydrothermal carbonization (HTC) is a promising technology for valuable resources
recovery from high-moisture wastes without pre-drying, while optimization of operational …
recovery from high-moisture wastes without pre-drying, while optimization of operational …
Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning
Conversion of wet organic wastes into renewable energy is a promising way to substitute
fossil fuels and avoid environmental deterioration. Hydrothermal carbonization and pyrolysis …
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 …
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
We introduce a modification of our previous 3D-to-2D fully convolutional architecture,
DeepSCAN, replacing batch normalization with instance normalization, and adding a …
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 …
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
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 …
most recent innovations in the recycling industry. The complementary strengths of Laser …
Deep learning regression for quantitative LIBS analysis
One of the most promising innovation strategies for sorting and recycling post-consumer
aluminium scrap is using quantitative Laser-Induced Breakdown Spectroscopy (LIBS) …
aluminium scrap is using quantitative Laser-Induced Breakdown Spectroscopy (LIBS) …
Kidney level lupus nephritis classification using uncertainty guided Bayesian convolutional neural networks
The kidney biopsy based diagnosis of Lupus Nephritis (LN) is characterized by low inter-
observer agreement, with misdiagnosis being associated with increased patient morbidity …
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 …
amount of data available. Supervised learning techniques cannot be applied without some …