Results 1 to 10 of about 192,949 (111)

Pulmonary Nodule Classification Using Feature and Ensemble Learning-Based Fusion Techniques

IEEE Access, 2021
The Pulmonary nodule indicates the presence of lung cancer. The deep convolutional neural networks (DCNNs) have been widely used to classify the pulmonary nodule as benign or malignant. However, an individual learner usually performs unsatisfactorily due
Muhammad Muzammil, Imdad Ali, Ihsan Ul Haq, Muhammad Amir, Suheel Abdullah   +4 more
doaj   +1 more source

Deep Feature Selection and Decision Level Fusion for Lungs Nodule Classification

IEEE Access, 2021
The existence of pulmonary nodules exhibits the presence of lung cancer. The Computer-Aided Diagnostic (CAD) and classification of such nodules in CT images lead to improve the lung cancer screening.
Imdad Ali, Muhammad Muzammil, Ihsan Ul Haq, Muhammad Amir, Suheel Abdullah   +4 more
doaj   +1 more source

Mitigating Virtualization Failures Through Migration to a Co-Located Hypervisor

IEEE Access, 2021
Many organizations are moving their systems to the cloud, where providers consolidate multiple clients using virtualization, which creates challenges to business-critical applications.
Frederico Cerveira, Raul Barbosa, Henrique Madeira   +2 more
doaj   +1 more source

Toward Building Trust in Machine Learning Models: Quantifying the Explainability by SHAP and References to Human Strategy

IEEE Access
Local model-agnostic Explainable Artificial Intelligence (XAI), such as LIME or SHAP, has recently gained popularity among researchers and data scientists for explaining black box Machine Learning (ML) models.
Zhaopeng Li, Mondher Bouazizi, Tomoaki Ohtsuki, Masakuni Ishii, Eri Nakahara   +4 more
doaj   +1 more source

A Critical Analysis on Vertebra Identification and Cobb Angle Estimation Using Deep Learning for Scoliosis Detection

IEEE Access
Scoliosis is a complicated spinal deformity, and millions of people are suffering from this disease worldwide. Early detection and accurate scoliosis assessment are vital for effective clinical management and patient outcomes.
Rakesh Kumar, Meenu Gupta, Ajith Abraham
doaj   +1 more source

Cloud Detection Method Based on Improved DeeplabV3+ Remote Sensing Image

IEEE Access
Cloud cover is a phenomenon that inevitably exists in remote sensing images, and ground information is lost due to the presence of clouds. To a large extent, it causes degradation of the remote sensing image quality. Therefore, the detection of clouds in
Jianguo Qian, Jinlong Ci, Hai Tan, Wenwen Xu, Yang Jiao, Peiyou Chen   +5 more
doaj   +1 more source

High-Resolution Stereoscopic Visualization of Pediatric Echocardiography Data on Microsoft HoloLens 2

IEEE Access
Three-dimensional ultrasound offers volumetric images and detailed anatomical data for medical diagnosis and treatment planning. It is a key tool in the medical field to obtain a comprehensive view of the body.
Meruja Selvamanikkam, Michelle Noga, Nee Scze Khoo, Kumaradevan Punithakumar   +3 more
doaj   +1 more source

Ultra-Efficient Edge Cardiac Disease Detection Towards Real-Time Precision Health

IEEE Access
Nowadays, intensive interests are targeting the deep learning on edge precision health towards instantaneous disease measurements. However, edge inference usually has constrained computing resource, which poses a great challenge on running the heavy deep
Junhua Wong, Jeanne Nerbonne, Qingxue Zhang   +2 more
doaj   +1 more source

Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset

IEEE Access
The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models.
Ummey Hany Ainan, Lip Yee Por, Yen-Lin Chen, Jing Yang, Chin Soon Ku   +4 more
doaj   +1 more source

The Weighted Group Consensus for a Kind of Discrete Heterogeneous Multi-Agent Systems With Time Delay and Packet Loss in Cooperative-Competitive Networks Based on Self-Adaptive Controller

IEEE Access
In this paper, the weighted group consensus for a kind of discrete heterogeneous multi-agent systems (HMASs) with packet loss in cooperative-competitive networks based on self-adaptive controller is studied. Based on self-adaptive controller, packet loss
Xia Sun, Leng Han, Shiyi Li, Jianli Yang, Xingcheng Pu   +4 more
doaj   +1 more source