Machine learning Techniques for Spondylolisthesis Diagnosis: a review by Rahma Rabee Aziz, Mohammed S. Jarjees, Mohammad R. Aziz, Ali Asim Hameed

“…The study shows the potential of computer-assisted methods for diagnosing spondylolisthesis, particularly in situations where qualified medical personnel are scarce. Machine learning techniques and deep learning models, including convolutional neural networks (CNNs), are utilized to accurately detect and assess spondylolisthesis. …”
Get full text

Estimating the Spectral Response of Eight-Band MSFA One-Shot Cameras Using Deep Learning by Pierre Gouton, Kacoutchy Jean Ayikpa, Diarra Mamadou

Get full text

An automatic classification of breast cancer using fuzzy scoring based ResNet CNN model by Nisha Y., Jagadeesh Gopal

“…The automated disease diagnosis system is proposed using a deep learning (DL) algorithm, which automates and helps speed up the process efficiently. …”
Get full text

Regional Heatwave Prediction Using Graph Neural Network and Weather Station Data by Peiyuan Li, Yin Yu, Daning Huang, Zhi‐Hua Wang, Ashish Sharma

“…In this paper, we propose a heatwave prediction algorithm based on a novel deep learning model, that is, Graph Neural Network (GNN). …”
Get full text

Time Evolution of Bacterial Resistance Observed with Principal Component Analysis by Claudia P. Barrera Patiño, Mitchell Bonner, Andrew Ramos Borsatto, Jennifer M. Soares, Kate C. Blanco, Vanderlei S. Bagnato

“…<b>Results</b>: The processing and data analysis with machine learning algorithms performed on this FTIR spectral database allowed for the identification of patterns across minimum inhibitory concentration (MIC) values associated with different exposure times and both clusters from hierarchical classification and PCA. …”
Get full text

Advancements in remote sensing technologies for accurate monitoring and management of surface water resources in Africa: an overview, limitations, and future directions by Maria Sigopi, Cletah Shoko, Timothy Dube

“…Additionally, machine learning (ML) algorithms, including support vector machines (SVM), Random Forest (RF), deep learning and emerging methodologies like recurrent tranformer networks, have been explored. …”
Get full text

Research on target localization and adaptive scrubbing of intelligent bathing assistance system by Ping Li, Ping Li, Shikai Feng, Hongliu Yu

Get full text

Data Mining Approaches in Predicting Entrepreneurial Intentions Based on Internet Marketing Applications by Milan Krivokuća, Mihalj Bakator, Dragan Ćoćkalo, Marijana Vidas-Bubanja, Vesna Makitan, Luka Djordjević, Borivoj Novaković, Stefan Ugrinov

“…Furthermore, a supervised machine learning algorithm, support vector machine (SVM) was used. …”
Get full text

Detect anomalous quartic gauge couplings at muon colliders with quantum kernel k-means by Shuai Zhang, Ke-Xin Chen, Ji-Chong Yang

“…In order to improve efficiency, machine learning algorithms have been introduced into the field of high-energy physics. …”
Get full text

Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…Comparative analysis revealed that traditional PCA methods risk losing essential pathological features by disregarding nonlinear data relationships, whereas deep learning requires substantial computational resources and high-quality datasets. …”
Get full text

Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…The contributions of this study lie in integrating LiDAR technology with advanced point cloud processing algorithms and a deep learning optimization model for vehicle damage assessment, demonstrating high precision and cost-effectiveness. …”
Get full text

Structural health monitoring based on three-dimensional point cloud technology: A systematic review by Yanzong Zhang, Guibo Nie, Duozhi Wang

“…It outlines the entire process, from data acquisition to modeling and visualization, and compares six core methods: geometric morphology analysis, multi-temporal differential analysis, feature extraction, mapping, machine learning, and deep learning. …”
Get full text

Evaluation of Global-Scale and Local-Scale Optimized Segmentation Algorithms in GEOBIA With SAM on Land Use and Land Cover by Tao He, Jianyu Chen, Linchong Kang, Qiankun Zhu

Get full text

A Short-Term Risk Prediction Method Based on In-Vehicle Perception Data by Xinpeng Yao, Nengchao Lyu, Mengfei Liu

“…Advanced driving assistance systems (ADASs) provide rich data on vehicles and their surroundings, enabling early detection and warning of driving risks. …”
Get full text

Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…While deep learning has shown state-of-the-art AD performance, its application in critical systems is hindered by concerns regarding training data efficiency, domain adaptation and interpretability. …”
Get full text

Roadside LiDAR Vehicle Detection and Tracking Using Range and Intensity Background Subtraction by Tianya Zhang, Peter J. Jin

“…In this study, we developed the solution of roadside LiDAR object detection using a combination of two unsupervised learning algorithms. …”
Get full text

The accuracy of image-based individual tree crown detection and delineation across vegetation types by N. Pucino, T. McVicar, S. Levick, A. van Dijk

“…<br />This study evaluates the performance of different ITS and Canopy Height Model (CHM) algorithms for generating large tree crown datasets using LiDAR-derived data from across Australia. …”
Get full text

A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…In addition to managing high-dimensional data, creating incremental and online clustering techniques, and investigating deep learning-based algorithms, the study suggests future research areas. …”
Get full text

Development of a Serum Metabolome‐Based Test for Early‐Stage Detection of Multiple Cancers by Rajnish Nagarkar, Mamillapalli Gopichand, Suparna Kanti Pal, Ankur Gupta, Najmuddin Md Saquib, Ahmad Ahmad, Ganga Sagar, Kanury V. S. Rao, Zaved Siddiqui, Imliwati Longkumer

“…After processing, the data were analyzed by our cancer detection machine‐learning algorithm to differentiate cancer from non‐cancer samples. …”
Get full text

Multi-Head Attention Based Bidirectional LSTM for Spelling Error Detection in the Indonesian Language by Yanfi Yanfi, Haryono Soeparno, Reina Setiawan, Widodo Budiharto

“…This study aims to address this gap by presenting a novel algorithm to improve spelling mistake detection within the Indonesian language context. …”
Get full text