Providing contexts for classification of transients in a wide-area sky survey: An application of noise-induced cluster ensemble by Tossapon Boongoen, Natthakan Iam-On, James Mullaney

“…Initial works based on the feature-based approach design this detection as imbalance classification, where a data-level method can be used to resolve the difference in cardinality between classes. …”
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Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds by Wu Qiao, Tong Xie, Jing Lu, Tinghan Jia

“…Using two data preprocessing methods and three feature extraction techniques, we constructed and validated models with eight machine learning algorithms. …”
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Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data by Mohammad Alemi, Alireza Bosaghzadeh, Fadi Dornaika

“…In this paper, we propose a novel GSSL algorithm tailored for large-scale databases, leveraging anchor points to mitigate the challenges posed by large affinity matrices. …”
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RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification by Yutong Wang, Ziming Kou, Cong Han, Yuchen Qin

“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. In response to the above, this article proposes a new “hardware friendly” coal gangue image recognition algorithm, RRBM-YOLO, which is combined with dark light enhancement. …”
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Transient Attracting Profiles in the Great Pacific Garbage Patch by L. Kunz, A. Griesel, C. Eden, R. Duran, R. Duran, B. Sainte-Rose

“…However, the concept remains unapplied since little is known about the persistence and attraction of these features, specifically within the Pacific. Therefore, we compute a 20-year dataset of daily TRAP detections from satellite-derived mesoscale velocities within the North Pacific subtropical gyre. …”
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THE ROLE OF DISPOSITION OF CONNECTING TISSUE IN THE RISE OF NONTRAUMATIC SUBARACHNOIDAL HEMORRHAGE IN YOUNG AGE by E. V. Petrova, T. F. Popova, I. A. Gribacheva, G. K. Taitubayeva

“…The obtained data can become a basis for developing an algorithm for screening physical examination of patients with an increased risk of aneurysmal hemorrhage.…”
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Proposed Method for Tracking Moon Phases using the Co-Occurrence Matrix by Abeer Thanoon

“…The proposed algorithm  of photographic and videoing treatment presents a method to trace the appearance of moon phases through the analysis of image texture using Co-Occurrence matrix after reading the video file followed by the representation of texture features in the form of histogram followed by the segmentation of image depending on the values of histogram to obtain the detection of the target , i.e. , the moon in order to trace the appearance of moon phases within a video serial and then know the area of the lighted part of the moon surface via sun rays through which the geometric shape of the lighted area of the moon along the video serial can be estimated in each stage . then the moon phase may be expected as it is a ratio of the estimated area of the geometric shape in relation to the total area of the circular disc of the full moon . the purposed method can be applied whenever a video film of the moon is available.…”
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A Novel Hybrid System Based on Fractal Coding for Soccer Retrieval from Video Database by Ehsan Lotfi

“…Experimental results show high accuracy of proposed caption extraction and player gathering detection algorithm and satisfying retrieval process.…”
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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

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
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Determination of Spatiotemporal Gait Parameters Using a Smartphone’s IMU in the Pocket: Threshold-Based and Deep Learning Approaches by Seunghee Lee, Changeon Park, Eunho Ha, Jiseon Hong, Sung Hoon Kim, Youngho Kim

“…This study proposes a hybrid approach combining threshold-based algorithm and deep learning to detect four major gait events—initial contact (IC), toe-off (TO), opposite initial contact (OIC), and opposite toe-off (OTO)—using only a smartphone’s built-in inertial sensor placed in the user’s pocket. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…This mechanism must overcome the multipath effect in multi-channel transmission to ensure accuracy and consistency when extracting action features. In this challenging context, innovative algorithms and model designs are crucial for addressing differences in CSI features between various actions and enhancing the model’s generalization ability and robustness.Method This study explores human actions’ physical and MIMO transmission characteristics, proposing a deep learning-based human action recognition method that employs a dual attention mechanism and a multi-channel, multi-scale fusion temporal convolution network to address the above challenges. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The methodology consists of three main phases: (i) data preprocessing, including anomaly detection and missing value handling; (ii) exploratory analysis to identify trends and correlations between PM concentrations (PMs) and predictor variables; and (iii) model development using 23 machine learning and deep learning algorithms, enhanced by 50 feature selection techniques. …”
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Attack traffic allocation and load balancing mechanism for SDN by LI Man, ZHOU Huachun, XU Qi, DENG Shuangxing, ZOU Tao, ZHANG Ruyun

“…This algorithm allocated traffic to different paths based on traffic and network features with the goal of reducing load and latency. …”
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Reconstruction of the object inhomogeneity parameters from near-field measurements in microwave tomography problem using neural networks by A.V. Medvedev, M.Yu. Medvedik

“…The problem posed is reduced to the Lippmann-Schwinger integral equation. A two-step algorithm is used to search for inhomogeneity. A neural network approach was used to filter the values obtained after a two-step algorithm. …”

Analysis of errors of the artificial horizon sensor based on vision system by A. A. Sheinikau, L. A. Ivanitski, V. A. Malkin

“…The article discusses the features of the practical implementation of the artificial horizon sensor based on the onboard vision system. …”
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Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition by Shaowei Shi, Kun Huang

“…First, we use an improved generative adversarial network to optimize heat map location detection of human key points. A human key point recognition algorithm is designed based on Transformer. …”
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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

“…Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. …”
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Estimating vegetation indices and biophysical parameters for Central European temperate forests with Sentinel-1 SAR data and machine learning by Daniel Paluba, Bertrand Le Saux, Francesco Sarti, Přemysl Štych

“…The inclusion of DEM-based auxiliary features and additional meteorological information improved the results. …”
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Diagnosis of Sleep Apnea Hypopnea Syndrome Using Fusion of Micro-motion Signals from Millimeter-wave Radar and Pulse Wave Data by Xiang ZHAO, Wei WANG, Chenyang LI, Jian GUAN, Gang LI

“…This study used a radar and pulse wave data preprocessing algorithm to extract time-frequency information and artificial features from the signals, balancing the accuracy and robustness of sleep-breathing abnormality event detection Additionally, a deep neural network was designed to fuse the two types of signals for precise identification of sleep apnea and hypopnea events, and to estimate the Apnea-Hypopnea Index (AHI) for quantitative assessment of sleep-breathing abnormality severity. …”
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Advances in optical biosensors as alternative diagnostics for clinical determination of ESKAPE bacteria by Maargavi Singh, Sreelakshmi C․S․, Chiranjay Mukhopadhyay, Sajan D. George, Pooja Nag, Kapil Sadani

“…In addition, incorporating artificial intelligence and machine learning algorithms in signal processing and feature extraction enhances biosensor performance and accelerates diagnostic accuracy. …”
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