Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems by Natalya Denissova, Serik Nurakynov, Olga Petrova, Daniker Chepashev, Gulzhan Daumova, Alena Yelisseyeva

“…Key data sources included satellite platforms such as Sentinel-1, Sentinel-2, TerraSAR-X, and Landsat-8, combined with machine learning, data fusion, and change detection algorithms to process and interpret the data. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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Comparison and Evaluation of Rain Gauge, CMORPH, TRMM PR and GPM DPR KuPR Precipitation Products over South China by Rui Wang, Huiping Li, Hao Huang, Liangliang Li

“…Several statistical metrics suggest that although the missing detection rates of TRMM and GPM are higher than those of CMORPH (probability of detection 10–60%), their false detection rates are spatially lower (false alert ratio 10–30%) in Middle-East China. …”
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State of Health Estimation of Li-Ion Battery via Incremental Capacity Analysis and Internal Resistance Identification Based on Kolmogorov–Arnold Networks by Jun Peng, Xuan Zhao, Jian Ma, Dean Meng, Shuhai Jia, Kai Zhang, Chenyan Gu, Wenhao Ding

“…Three commonly used machine learning methods (BP, LSTM, TCN) and two hybrid algorithms (LSTM-KAN and TCN-KAN) were used to establish the SOH estimation model. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…In recent years, the integration of artificial intelligence (AI) with radiomics has significantly enhanced the process of analyzing and extracting meaningful features from large and complex radiomic datasets through the application of machine learning (ML) and deep learning (DL) algorithms. …”
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Gamified mHealth System for Evaluating Upper Limb Motor Performance in Children: Cross-Sectional Feasibility Study by Md Raihan Mia, Sheikh Iqbal Ahamed, Samuel Nemanich

“…We applied change point detection (ie, the pruned exact linear time method), signal processing techniques, and other algorithms to calculate movement speed and accuracy from spatiotemporal parameters. …”
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Technical advantages bridging the preservation limits of painted decoration of Neolithic ceramic figurines by Ludmila Kaňáková, Vojtěch Nosek, Attila Kreiter, László Előd Aradi, Martin Košťál

“…By applying DStretch to high-resolution photographs or 3D model textures, pigment residues can be identified without damaging the object. The algorithm’s versatility extends to different colour channels, making it possible to detect subtle traces across different pigments, improving overall data preservation and analysis. 378 fragments of Neolithic ceramic figurines from the Lengyel culture site Těšetice-Kyjovice – Sutny, the largest known collection in central Europe, have been studied. …”
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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…This allows robust scan registration to take place in the presence of unknown point correspondences and inter-scan translation and orientation as well as point cloud detection and spatial errors. The resulting Particle Swarm Optimization (PSO)-COLA registration algorithm is capable of determining inter-scan point correspondences, but can also run based on point correspondences determined by other algorithms, such as the application of Fast Point Feature Histograms (FPFH) descriptors. …”
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Implementation of automation tools for test analysis in the Radiotherapy Quality Assurance Programs by João Guilherme Rivera Santiago, Laura Furnari, Marcus Vinicius Saad de Paula Rodrigues, Victor Augusto Bertotti Ribeiro

“…To implement such tools, it is essential to assess factors such as accuracy, error detection sensitivity, adaptability to institution needs, and ease of access and use for those involved in quality control processes. …”
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Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment by Paweł Tysiąc, Rafał Ossowski, Łukasz Janowski, Damian Moskalewicz

“…Our approach included change detection analysis to estimate eroded areas. Next, by applying Random Forest classifier within Google Earth Engine, we evaluated the importance of features in detecting these degraded zones. …”
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Epigenetic modifications of cfDNA in liquid biopsy for the cancer care continuum by Jodie Wong, Rohit Muralidhar, Liang Wang, Chiang-Ching Huang

“…Such cooperative efforts are essential to fully leverage the potential of epigenetic features in clinical practice.…”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…The outcome emphasizes its ability to identify the most effective solution for crack detection in practical scenarios, where PCA-based feature selection improves computational efficiency without compromising performance. …”
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Hybrid Series of Carbon‐Vacancy Electrodes for Multi Chemical Vapors Diagnosis Using a Residual Multi‐Task Model by Tianci Liu, Yun Ji Hwang, Lu Zhang, Jongwoo Hong, Teajong Hwang, Seong Chan Jun

“…However, substantial challenges and opportunities remain in the simultaneous detection and classification of multiple gases. Artificial intelligence (AI) integrated gas sensor systems effectively enable multi‐gas detection using specialized algorithms. …”
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An intelligent IDS using bagging based fuzzy CNN for secured communication in vehicular networks by M. Anand, S. Muthurajkumar

“…Hence, an efficient Feature Selection Algorithm named Weightage and Ranking Based Feature Selection Algorithm and a Bagging based Fuzzy Convolutional Neural Network classification algorithm with Adam optimizer are proposed in this article which are used to identify the attacks more effectively using bagging with fuzzy inference in the deep convolutional neural network classifier. …”
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Enhanced Magnetic Resonance Imaging-Based Brain Tumor Classification with a Hybrid Swin Transformer and ResNet50V2 Model by Abeer Fayez Al Bataineh, Khalid M. O. Nahar, Hayel Khafajeh, Ghassan Samara, Raed Alazaidah, Ahmad Nasayreh, Ayah Bashkami, Hasan Gharaibeh, Waed Dawaghreh

“…Effective brain cancer detection is crucial for patients’ safety and health. …”
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Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

“…This algorithm, based on YOLOv5s, utilizes the lightweight MobileNetV3-Small network to replace the original YOLOv5s feature extraction backbone network, thereby improving the detection speed. …”
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Comprehensive Blood Metabolome and Exposome Analysis, Annotation, and Interpretation in E-Waste Workers by Zhiqiang Pang, Charles Viau, Julius N. Fobil, Niladri Basu, Jianguo Xia

“…A specialized computational workflow was established for exposomics data analysis, incorporating two curated reference libraries for metabolome and exposome profiling. Two feature detection algorithms, <i>asari</i> and <i>centWave</i>, were applied. …”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…However, this traditional approach captures only a limited set of features of ECG and thereby limits the effectiveness of DL architectures in disease detection.MethodsThis work proposes “BlendNet,” a DL architecture that effectively extracts the features of an ECG signal using a blending approach termed “alpha blending.” …”
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Speckle Noise Removal in OCT Images via Wavelet Transform and DnCNN by Fangfang Li, Qizhou Wu, Bei Jia, Zhicheng Yang

“…This reconstruction step maintains structural integrity and enhances diagnostic clarity by preserving essential spatial features. (3) Results: The MSE, PSNR, and SSIM indices of the proposed algorithm in this paper were 4.9052, 44.8603, and 0.9514, respectively, achieving commendable results compared to other algorithms. …”
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