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[HTML][HTML] Multi-input dual-stream capsule network for improved lung and colon cancer classification
Lung and colon cancers are two of the most common causes of death and morbidity in
humans. One of the most important aspects of appropriate treatment is the histopathological …
humans. One of the most important aspects of appropriate treatment is the histopathological …
Robustness fine-tuning deep learning model for cancers diagnosis based on histopathology image analysis
Histopathology is the most accurate way to diagnose cancer and identify prognostic and
therapeutic targets. The likelihood of survival is significantly increased by early cancer …
therapeutic targets. The likelihood of survival is significantly increased by early cancer …
[HTML][HTML] On urinary bladder cancer diagnosis: Utilization of deep convolutional generative adversarial networks for data augmentation
Urinary bladder cancer is one of the most common urinary tract cancers. Standard diagnosis
procedure can be invasive and time-consuming. For these reasons, procedure called optical …
procedure can be invasive and time-consuming. For these reasons, procedure called optical …
[HTML][HTML] Automatic evaluation of the lung condition of COVID-19 patients using X-ray images and convolutional neural networks
COVID-19 represents one of the greatest challenges in modern history. Its impact is most
noticeable in the health care system, mostly due to the accelerated and increased influx of …
noticeable in the health care system, mostly due to the accelerated and increased influx of …
The registration of visible and thermal images through multi-objective optimization
Multimodal imaging with visible and thermal sensors attracts much attention due to its
robustness under challenging illumination conditions. Due to spectral differences, the visible …
robustness under challenging illumination conditions. Due to spectral differences, the visible …
Predicting greenhouse gas fluxes in coastal salt marshes using artificial neural networks
MT Zaki, OI Abdul-Aziz - Wetlands, 2022 - Springer
Prediction of wetland greenhouse gas (GHG) fluxes has been a challenging undertaking.
Machine learning techniques such as the artificial neural network (ANN) has a strong …
Machine learning techniques such as the artificial neural network (ANN) has a strong …
Energy and Exergy Analysis of Waste Heat Recovery Closed-Cycle Gas Turbine System while Operating with Different Medium
Sažetak In this paper is performed energy and exergy analysis of waste heat recovery
closed-cycle gas turbine system. Analyzed system can use waste heat from various main …
closed-cycle gas turbine system. Analyzed system can use waste heat from various main …
Automated grading of oral squamous cell carcinoma into multiple classes using deep learning methods
J Musulin, D Štifanić, A Zulijani… - 2021 IEEE 21st …, 2021 - ieeexplore.ieee.org
The diagnosis of oral squamous cell carcinoma is based on a histopathological
examination, which is still the most reliable way of identifying oral cancer despite its high …
examination, which is still the most reliable way of identifying oral cancer despite its high …
Thermodynamic Analysis of a Condensate Heating System from a Marine Steam Propulsion Plant with Steam Reheating
The thermodynamic (energy and exergy) analysis of a condensate heating system, its
segments, and components from a marine steam propulsion plant with steam reheating is …
segments, and components from a marine steam propulsion plant with steam reheating is …
[PDF][PDF] Prediction of robot grasp robustness using artificial intelligence algorithms
Predicting the quality of the robot end-effector grasp quality during an industrial robot
manipulator operation can be an extremely complex task. As is often the case with such …
manipulator operation can be an extremely complex task. As is often the case with such …