UNS Geo: LiDAR Dataset for point cloud classification in urban areas by M. Govedarica, G. Jakovljevic, I. Ruskoviski, V. Pajic

“…The classification of the urban point cloud is an essential task for numerous applications, including mapping, 3D urban modelling, etc.. Although in the last few years, different methodologies and algorithms have been proposed, precise and detailed point cloud labelling is still challenging. …”
Get full text

A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…Additionally, a hybrid classification approach is introduced, combining Autoencoder (AE) with the Butterfly Optimization Algorithm (BOA) to enhance detection accuracy. To manage and process large datasets effectively, the MapReduce tool is used for efficient data handling. …”
Get full text

Estimation of Anthocyanins in Apple Leaves Based on Ground Hyperspectral Imaging and Machine Learning Models by Yu Zhang, Mi Zou, Yanjun Li, Qingrui Chang, Xing Chen, Zhiyong Dai, Weihao Yuan

“…The original hyperspectral imaging at wavelengths before 720 nm shows a decrease in reflectance as the growth stages progress, while the spectral curves after 720 nm remain largely consistent across stages; (2) Compared to single original spectral variables, multivariate estimation models using original spectra and second-order derivative transformed spectra show improved accuracy for anthocyanins estimation across different growth stages, with the most significant improvement during the Fruit Enlargement stage; (3) Although the computation of the three-band spectral indices is resource-intensive and time-consuming, it can enhance anthocyanins estimation accuracy; (4) Among all models, the CatBoost model based on original spectra and second-order derivative transformed spectra indices for the entire growth period achieved the highest accuracy, with a validation set R² of 0.934 and a RPD of 3.888, and produced effective leaf anthocyanins inversion maps. …”
Get full text

Rapid global fitting of large fluorescence lifetime imaging microscopy datasets. by Sean C Warren, Anca Margineanu, Dominic Alibhai, Douglas J Kelly, Clifford Talbot, Yuriy Alexandrov, Ian Munro, Matilda Katan, Chris Dunsby, Paul M W French

“…Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. …”
Get full text

Application of YOLO11 Model with Spatial Pyramid Dilation Convolution (SPD-Conv) and Effective Squeeze-Excitation (EffectiveSE) Fusion in Rail Track Defect Detection by Weigang Zhu, Xingjiang Han, Kehua Zhang, Siyi Lin, Jian Jin

“…The mean Average Precision (mAP@0.5) of the improved algorithm on track fastener dataset and track surface dataset reached 95.9% and 89.5%, respectively, which not only surpasses the original YOLO11 model but also outperforms other widely used object detection algorithms. …”
Get full text

A Ship Heading Estimation Method Based on DeepLabV3+ and Contrastive Learning-Optimized Multi-Scale Similarity by Weihao Tao, Yasong Luo, Jijin Tong, Qingtao Xia, Jianjing Qu

“…The framework introduces the Multi-Scale Structural Similarity (MS-SSIM) algorithm enhanced by a triplet contrastive learning mechanism that dynamically optimizes feature weights across scales, thereby improving robustness against image degradation and partial occlusion. …”
Get full text

The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration by Yong Liu, Xueyan Chen, Jingwen Chen, Chao Song, Zhangchao Wei, Zongchao Liu, Fei Liu

“…Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM‐RFE algorithm to identify core MAPK‐related genes. …”
Get full text

Intelligent Detection of Tomato Ripening in Natural Environments Using YOLO-DGS by Mengyuan Zhao, Beibei Cui, Yuehao Yu, Xiaoyi Zhang, Jiaxin Xu, Fengzheng Shi, Liang Zhao

“…This module performs convolution in stages on the feature map, generating more feature maps with fewer parameters and computational resources, thereby improving the model’s feature extraction capability while reducing parameter count and computational cost. …”
Get full text

A Conceptual Framework for Planning Road Digital Twins by Munkhbaatar Buuveibaatar, Ioannis Brilakis, Matt Peck, George Economides, Wonhee Lee

“…Digital twin (DT) is an emerging technology gaining traction across various industries. However, its development and application in the architecture, engineering, and construction (AEC) industry remain in their early stage, lagging considerably behind other sectors. …”
Get full text

Multi-Agent Reinforcement Learning in Games: Research and Applications by Haiyang Li, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, Donglin Zhu

“…Building upon stochastic game and extensive-form game-theoretic frameworks, we establish a methodological taxonomy across three dimensions: value function optimization, policy gradient learning, and online search planning, thereby clarifying the evolutionary logic and innovation trajectories of algorithmic advancements. …”
Get full text

Hyperspectral imagery quality assessment and band reconstruction using the prophet model by Ping Ma, Jinchang Ren, Zhi Gao, Yinhe Li, Rongjun Chen

“…In a head‐to‐head comparison, the framework against six state‐of‐the‐art band reconstruction algorithms including three spectral methods, two spatial‐spectral methods and one deep learning method is benchmarked. …”
Get full text

METHODOLOGICAL APPROACH TO CONSTRUCTION OF A SYSTEM FOR DETECTION AND PREVENTION OF DESTRUCTION OF THE ACTIVITIES OF CONSTRUCTION PARTICIPANTS by Mykhailo Malykhin, Denys Dubinin, Olha Bielienkova

“…The methodological foundation of the research combines system analysis, risk-oriented modelling, and process mapping techniques. The proposed framework incorporates the utilisation of behavioural indicators, deviation tracking algorithms, and early warning dashboards, which collectively facilitate proactive responses to disruption risks. …”
Get full text

Sequential Hybrid Integration of U-Net and Fully Convolutional Networks with Mask R-CNN for Enhanced Building Boundary Segmentation from Satellite Imagery by Rojgar Qarani Ismael, Haval Abduljabbar Sadeq

“… In the recent years, building boundary segmentation obtained significant advancement through using deep learning. The present algorithms, such as Convolutional Neural Network (CNN) are unable to detect buildings in challenging urban areas like occlusions. …”
Get full text

AI-Powered Vocalization Analysis in Poultry: Systematic Review of Health, Behavior, and Welfare Monitoring by Venkatraman Manikandan, Suresh Neethirajan

“…Through rigorous bibliometric co-occurrence mapping and thematic clustering analysis, this review exposes persistent methodological bottlenecks: dataset standardization deficits, evaluation protocol inconsistencies, and algorithmic interpretability limitations. …”
Get full text

Artificial intelligence in environmental monitoring: in-depth analysis by Emran Alotaibi, Nadia Nassif

“…In-depth analysis reveals advancements in AI/ML methodologies, including novel algorithms for soil mapping, land-cover classification, flood susceptibility modeling, and remote sensing image analysis. …”
Get full text

Machine learning-based spatio-temporal assessment of land use/land cover change in Barishal district of Bangladesh between 1988 and 2024 by Walida Zaman, H Rainak Khan Real

“…The performance of four machine learning algorithms (Support Vector Machine, Classification and Regression Tree, K-Nearest Neighbor, and Random Forests) were evaluated to ensure classification reliability. …”
Get full text

Constructing the commuting backbone network dataset for the United States by Jinpeng Wang, Yujie Hu

“…Using the disparity filter algorithm, the study extracts significant commuter flows—forming the commuter connection backbone network—within core-based statistical areas (CBSAs). …”
Get full text

Unraveling the co-morbidity between COVID-19 and neurodegenerative diseases through multi-scale graph analysis: A systematic investigation of biological databases and text mining by Negin Sadat Babaiha, Stefan Geissler, Vincent Nibart, Heval Atas Güvenilir, Vinay Srinivas Bharadhwaj, Alpha Tom Kodamullil, Juergen Klein, Marc Jacobs, Martin Hofmann-Apitius

Get full text

User Quality of Experience (QoE) Satisfaction for Video Content Selection (VCS) Framework in Smartphone Devices by Muhamad Hanif Jofri, Ida Aryanie Bahrudin, Noor Zuraidin Mohd Safar, Juliana Mohamed, Abdul Halim Omar

“…We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. …”
Get full text

Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…Abstract Background Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife (CK) is essential for precise planning. …”
Get full text