Reliable Event Detection via Multiple Edge Computing on Streaming Traffic Social Data by Yipeng Ji, Jingyi Wang, Yan Niu, Hongyuan Ma

Get full text

Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…In this study, a binary version of the Advanced Al-Biruni Earth Radius (bABER) algorithm is proposed for the intelligent removal of unnecessary data and identifying the most essential features for cancer detection. …”
Get full text

A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…Diseased people experience severe symptoms in more severe cases. such as shortness of breath, which can lead to respiratory failure and death. Machine learning techniques for detection and classification are commonly used in current medical diagnoses. …”
Get full text

Evaluation and Improvement of Generalization Performance of SAR Ship Recognition Algorithms by Chi Zhang, Xi Zhang, Jie Zhang, Gui Gao, Yongshou Dai, Genwang Liu, Yongjun Jia, Xiaochen Wang, Yi Zhang, Meng Bao

Get full text

Optimal feature‐algorithm combination research for EEG fatigue driving detection based on functional brain network by Yi Zhou, ChangQing Zeng, ZhenDong Mu

“…Then, five functional brain network features (clustering coefficient, node degree, eccentricity, local efficiency, and characteristic path length) are extracted and combined to obtain a total of 26 features and eight machine learning algorithms (SVM, LR, DT, RF, KNN, LDA, ADB, GBM) are used as classifiers for fatigue detection respectively. …”
Get full text

IoT-edge anomaly detection for covariate shifted and point time series health data by Partha Pratim Ray, Dinesh Dash

“…We implement the ”IRKernel” to investigate the efficiency of exponentially weighted moving average (EWMA)-based light-weight statistical learning by using three variants e.g. probabilistic (P), shift-detect (SD), and two-stage shift-detect (TS-SD) over the EWMA algorithms. …”
Get full text

Machine learning anomaly detection of lost and unaccounted for gas in natural gas networks by Omar Fayez Mohamed ElMahdy, Mohamed Ezz Hassan, Sayed M. Metwalli

“…A machine learning anomaly detection algorithm using multivariate Gaussian density estimation combined with principal component analysis (PCA) is developed. …”
Get full text

Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection by Rani Kurnia Putri, Muhammad Athoillah*

“…Deep Learning works by representing data in layers of learning layers so that the representation becomes more meaningful, and Support Vector Machine tries to find the hyperplane that maximizes the margin between the hyperplane and the closest data points from each class so that the classification becomes more accurate. …”
Get full text

A Federated Learning Model for Detecting Cyberattacks in Internet of Medical Things Networks by Abdallah Ghourabi, Adel Alkhalil

“…In this paper, we propose a novel approach based on Federated Learning (FL), enabling medical devices to collaboratively detect cyberattacks without directly sharing sensitive data. …”
Get full text

Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Besides, this research aims to investigate the feasibility that employs data mining framework together with optimization algorithms as approaches towards plant diseases identification and categorization systems. …”
Get full text

An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…With the increasing application of machine learning technology in the medical field, algorithm-based diagnostic tools provide new possibilities for early prediction of breast cancer. …”
Get full text

Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections by Oona Rainio, Heidi Huhtanen, Jari-Pekka Vierula, Janne Nurminen, Jaakko Heikkinen, Mikko Nyman, Riku Klén, Jussi Hirvonen

“…This study aimed to develop a deep learning-based algorithm for the automated detection of RPE. …”
Get full text

Automated Damage Detection on Concrete Structures Using Computer Vision and Drone Imagery by Timothy Malche, Sumegh Tharewal, Rajesh Kumar Dhanaraj

Get full text

YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

Get full text

Anomaly detection with domain specific shapelet learning for sucker rod pump system by Xiangyu Li, Zhupei Liao, Chunhua Yuan

“…This paper proposes an unsupervised end-to-end learning algorithm designed for SRPS anomaly detection, denoted Anomaly Detection with Domain-specific Shapelet Learning algorithm (AD-DSL). …”
Get full text

A hybrid machine learning and ied-based fault detection scheme for microgrids by Hamid Radmanesh, Abolfazl Hadadi

“…Additionally, the proposed algorithm achieves higher fault detection speed and improved computational efficiency compared to other methods. …”
Get full text

A Comparative Study of Machine Learning Based Classifications on Lung Cancer Detection by A. Rakesh, Radhamani Ellapparaj

“…The research employs a rigorous methodology that involves the systematic exploration of various machine learning algorithms applied to a comprehensive lung cancer dataset. …”
Get full text

Automatic Detection Method for Surface Diseases of Shield Tunnel Based on Deep Learning by WANG Baokun, WANG Rulu, CHEN Jinjian, PAN Yue, WANG Lujie

“…The experimental results indicate that the proposed SU-ResNet++ algorithm is applicable to the detection of shield tunnel disease data, and can automatically and accurately identify the disease category and form. …”
Get full text

An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation by Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee

“…To address these challenges, this paper introduces an innovative framework called the Optimized Multi-Task Contrastive Learning Framework (OMCLF), which leverages self-supervised learning (SSL) and genetic algorithms (GA) to enhance HIFU lesion detection and segmentation. …”
Get full text

The Automatic Detection of Pedestrians under the High-Density Conditions by Deep Learning Techniques by Cheng-Jie Jin, Xiaomeng Shi, Ting Hui, Dawei Li, Ke Ma

“…Therefore, we utilized one emerging method based on the deep learning algorithm. Based on the top-view video data of some pedestrian flow experiments recorded by an unmanned aerial vehicle (UAV), we produce our own training datasets. …”
Get full text