Computer vision and machine learning methods for heat transfer and fluid flow in complex structural microchannels: A review
B Yang, X Zhu, B Wei, M Liu, Y Li, Z Lv, F Wang - Energies, 2023 - mdpi.com
Heat dissipation in high-heat flux micro-devices has become a pressing issue. One of the
most effective methods for removing the high heat load of micro-devices is boiling heat …
most effective methods for removing the high heat load of micro-devices is boiling heat …
A voting-based ensemble deep learning method focusing on image augmentation and preprocessing variations for tuberculosis detection
E Tasci, C Uluturk, A Ugur - Neural Computing and Applications, 2021 - Springer
Tuberculosis (TB) is known as a potentially dangerous and infectious disease that affects
mostly lungs worldwide. The detection and treatment of TB at an early stage are critical for …
mostly lungs worldwide. The detection and treatment of TB at an early stage are critical for …
Deep and hybrid learning technique for early detection of tuberculosis based on X-ray images using feature fusion
Tuberculosis (TB) is a fatal disease in developing countries, with the infection spreading
through direct contact or the air. Despite its seriousness, the early detection of tuberculosis …
through direct contact or the air. Despite its seriousness, the early detection of tuberculosis …
Multi-techniques for analyzing x-ray images for early detection and differentiation of pneumonia and tuberculosis based on hybrid features
An infectious disease called tuberculosis (TB) exhibits pneumonia-like symptoms and traits.
One of the most important methods for identifying and diagnosing pneumonia and …
One of the most important methods for identifying and diagnosing pneumonia and …
Early diagnosis of respiratory system diseases (RSD) using deep convolutional neural networks
The evaluation of respiratory system disorders and their classification has been to be one of
the most significant investigated topics in recent years. Medical scan dataset sizes are …
the most significant investigated topics in recent years. Medical scan dataset sizes are …
COFE-Net: an ensemble strategy for computer-aided detection for COVID-19
Biomedical images contain a large volume of sensor measurements, which can reveal the
descriptors of the disease under investigation. Computer-based analysis of such …
descriptors of the disease under investigation. Computer-based analysis of such …
Ensemble deep learning for the detection of covid-19 in unbalanced chest x-ray dataset
The ongoing COVID-19 pandemic has caused devastating effects on humanity worldwide.
With practical advantages and wide accessibility, chest X-rays (CXRs) play vital roles in the …
With practical advantages and wide accessibility, chest X-rays (CXRs) play vital roles in the …
ViT-TB: ensemble learning based ViT model for tuberculosis recognition
Dynamic modern healthcare systems rely heavily on the contributions of computer scientists.
The diagnosis process is a team effort involving many people: patients, their families …
The diagnosis process is a team effort involving many people: patients, their families …
A deep learning‐based x‐ray imaging diagnosis system for classification of tuberculosis, COVID‐19, and pneumonia traits using evolutionary algorithm
To aid in detection of tuberculosis, researchers have concentrated on developing computer‐
aided diagnostic technologies based on x‐ray imaging. Since it generates noninvasive …
aided diagnostic technologies based on x‐ray imaging. Since it generates noninvasive …
Early diagnosis of tuberculosis using deep learning approach for iot based healthcare applications
G Simi Margarat, G Hemalatha, A Mishra… - Computational …, 2022 - Wiley Online Library
In the modern world, Tuberculosis (TB) is regarded as a serious health issue with a high rate
of mortality. TB can be cured completely by early diagnosis. For achieving this, one tool …
of mortality. TB can be cured completely by early diagnosis. For achieving this, one tool …