[HTML][HTML] A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images
K Jabeen, MA Khan, MA Hameed, O Alqahtani… - Frontiers in …, 2024 - frontiersin.org
With over 2.1 million new cases of breast cancer diagnosed annually, the incidence and
mortality rate of this disease pose severe global health issues for women. Identifying the …
mortality rate of this disease pose severe global health issues for women. Identifying the …
Discrete ripplet-II transform feature extraction and metaheuristic-optimized feature selection for enhanced glaucoma detection in fundus images using least square …
Recently, significant progress has been made in developing computer-aided diagnosis
(CAD) systems for identifying glaucoma abnormalities using fundus images. Despite their …
(CAD) systems for identifying glaucoma abnormalities using fundus images. Despite their …
[HTML][HTML] TfELM: Extreme Learning Machines framework with Python and TensorFlow
K Struniawski, R Kozera - SoftwareX, 2024 - Elsevier
TfELM introduces an innovative Python framework leveraging TensorFlow for Extreme
Learning Machines (ELMs), offering a comprehensive suite for diverse machine learning …
Learning Machines (ELMs), offering a comprehensive suite for diverse machine learning …
Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Glaucoma is defined as progressive optic neuropathy that damages the structural
appearance of the optic nerve head and is characterized by permanent blindness. For mass …
appearance of the optic nerve head and is characterized by permanent blindness. For mass …
Ohabm-net: an enhanced attention-driven hybrid network for improved breast mass detection
Breast cancer begins in the breast tissues and can progressively spread to other parts of the
body. Early detection is crucial, as it allows for timely treatment, potentially saving lives …
body. Early detection is crucial, as it allows for timely treatment, potentially saving lives …
A Mine Water Source Prediction Model Based on LIF Technology and BWO-ELM
P Yan, G Li, W Wang, Y Zhao, J Wang, Z Wen - Journal of Fluorescence, 2024 - Springer
The traditional methods for identifying water sources in coal mines lack the ability to quickly
detect water sources and are prone to causing secondary pollution of samples. In contrast …
detect water sources and are prone to causing secondary pollution of samples. In contrast …
Empirical Evaluation of Deep Learning Techniques for Fish Disease Detection in Aquaculture Systems: A Transfer Learning and Fusion-Based Approach
In aquatic environments, the health of fish populations is crucial for maintaining ecological
balance and sustaining aquaculture industries. Timely and accurately detecting fish …
balance and sustaining aquaculture industries. Timely and accurately detecting fish …
Enhancing Skin Cancer Diagnosis with Customized InceptionV3: A Deep Learning Approach
Skin cancer, a common and dangerous health issue, often requires accurate detection for
effective treatment. Traditional machine learning techniques, while useful, involve …
effective treatment. Traditional machine learning techniques, while useful, involve …
Customized VGG16: Enhancing Breast Cancer Diagnosis Through Deep Learning Techniques
Breast cancer is a major worldwide health concern, which emphasizes the necessity for
accurate and effective diagnostic instruments. Using deep learning techniques, this study …
accurate and effective diagnostic instruments. Using deep learning techniques, this study …
Automated Breast Cancer Detection Model: A Novel Customized AlexNet Model
Breast cancer poses a significant global health challenge, underscoring the need for
effective diagnostic tools. This study introduces an automated breast cancer detection …
effective diagnostic tools. This study introduces an automated breast cancer detection …