[HTML][HTML] Deep neural network pulmonary nodule segmentation methods for CT images: Literature review and experimental comparisons

L Zhi, W Jiang, S Zhang, T Zhou - Computers in Biology and Medicine, 2023 - Elsevier
Automatic and accurate segmentation of pulmonary nodules in CT images can help
physicians perform more accurate quantitative analysis, diagnose diseases, and improve …

Fully convolutional network for the semantic segmentation of medical images: A survey

SY Huang, WL Hsu, RJ Hsu, DW Liu - Diagnostics, 2022 - mdpi.com
There have been major developments in deep learning in computer vision since the 2010s.
Deep learning has contributed to a wealth of data in medical image processing, and …

A deep learning framework for leukemia cancer detection in microscopic blood samples using squeeze and excitation learning

M Bukhari, S Yasmin, S Sammad… - Mathematical …, 2022 - Wiley Online Library
Leukemia is a fatal category of cancer‐related disease that affects individuals of all ages,
including children and adults, and is a significant cause of death worldwide. Particularly, it is …

Emotion recognition framework using multiple modalities for an effective human–computer interaction

A Moin, F Aadil, Z Ali, D Kang - The Journal of Supercomputing, 2023 - Springer
Human emotions are subjective reactions to objects or events that are related to diverse
physiological, behavioral and intellectual changes. The research community is gaining more …

[HTML][HTML] An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning

M Maqsood, S Yasmin, S Gillani, F Aadil, I Mehmood… - ISA transactions, 2023 - Elsevier
Gait identification based on Deep Learning (DL) techniques has recently emerged as
biometric technology for surveillance. We leveraged the vulnerabilities and decision-making …

DEHA-Net: A Dual-Encoder-Based Hard Attention Network with an Adaptive ROI Mechanism for Lung Nodule Segmentation

M Usman, YG Shin - Sensors, 2023 - mdpi.com
Measuring pulmonary nodules accurately can help the early diagnosis of lung cancer, which
can increase the survival rate among patients. Numerous techniques for lung nodule …

[PDF][PDF] An Automated Real-Time Face Mask Detection System Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic.

MFS Sabir, I Mehmood, WA Alsaggaf… - … , Materials & Continua, 2022 - researchgate.net
Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis.
According to the World Health Organization (WHO), people in public places should wear a …

Analyzing the stock exchange markets of EU nations: A case study of brexit social media sentiment

H Maqsood, M Maqsood, S Yasmin, I Mehmood… - Systems, 2022 - mdpi.com
Stock exchange analysis is regarded as a stochastic and demanding real-world setting in
which fluctuations in stock prices are influenced by a wide range of aspects and events. In …

DAS-Net: A lung nodule segmentation method based on adaptive dual-branch attention and shadow mapping

S Luo, J Zhang, N Xiao, Y Qiang, K Li, J Zhao… - Applied …, 2022 - Springer
Quantitative analysis of pulmonary nodules is necessary for the early diagnosis and
treatment of lung cancer, improving the possibility of patient survival. Although deep …

Ct lung nodule segmentation: A comparative study of data preprocessing and deep learning models

W Chen, Y Wang, D Tian, Y Yao - IEEE Access, 2023 - ieeexplore.ieee.org
The number of deaths from lung cancer reached 1.8 million in 2020, ranking first among all
cancers. Early diagnosis has been found to improve the survival rate of lung cancer patients …