Defense strategies for adversarial machine learning: A survey
Abstract Adversarial Machine Learning (AML) is a recently introduced technique, aiming to
deceive Machine Learning (ML) models by providing falsified inputs to render those models …
deceive Machine Learning (ML) models by providing falsified inputs to render those models …
Pneumonia detection in chest X-ray images using an ensemble of deep learning models
Pneumonia is a respiratory infection caused by bacteria or viruses; it affects many
individuals, especially in developing and underdeveloped nations, where high levels of …
individuals, especially in developing and underdeveloped nations, where high levels of …
Adversarial examples: attacks and defences on medical deep learning systems
MK Puttagunta, S Ravi… - Multimedia Tools and …, 2023 - Springer
In recent years, significant progress has been achieved using deep neural networks (DNNs)
in obtaining human-level performance on various long-standing tasks. With the increased …
in obtaining human-level performance on various long-standing tasks. With the increased …
ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images
For the clinical diagnosis, it is essential to obtain accurate morphology data of retinal blood
vessels from patients, and the morphology of retinal blood vessels can well help doctors to …
vessels from patients, and the morphology of retinal blood vessels can well help doctors to …
[HTML][HTML] Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images
MR Islam, LF Abdulrazak, M Nahiduzzaman… - Computers in biology …, 2022 - Elsevier
Diabetic Retinopathy (DR) is a major complication in human eyes among the diabetic
patients. Early detection of the DR can save many patients from permanent blindness …
patients. Early detection of the DR can save many patients from permanent blindness …
Image-based malware classification using VGG19 network and spatial convolutional attention
In recent years the amount of malware spreading through the internet and infecting
computers and other communication devices has tremendously increased. To date …
computers and other communication devices has tremendously increased. To date …
NSL-MHA-CNN: a novel CNN architecture for robust diabetic retinopathy prediction against adversarial attacks
O Daanouni, B Cherradi, A Tmiri - IEEE Access, 2022 - ieeexplore.ieee.org
Convolution Neural Network (CNN) models have gained ground in research activities
particularly in medical images used for Diabetes Retinopathy (DR) detection. X-ray, MRI …
particularly in medical images used for Diabetes Retinopathy (DR) detection. X-ray, MRI …
A novel text2IMG mechanism of credit card fraud detection: A deep learning approach
A Alharbi, M Alshammari, OD Okon, A Alabrah… - Electronics, 2022 - mdpi.com
Online sales and purchases are increasing daily, and they generally involve credit card
transactions. This not only provides convenience to the end-user but also increases the …
transactions. This not only provides convenience to the end-user but also increases the …
Mayfly optimization with deep learning enabled retinal fundus image classification model
Retinal fundus images are widely employed to screen for various eye diseases, giving them
significant clinical importance. Investigation of medical images has been considerably …
significant clinical importance. Investigation of medical images has been considerably …
[PDF][PDF] A quantization assisted U-Net study with ICA and deep features fusion for breast cancer identification using ultrasonic data
Breast cancer is one of the leading causes of death in women worldwide—the rapid
increase in breast cancer has brought about more accessible diagnosis resources. The …
increase in breast cancer has brought about more accessible diagnosis resources. The …