Multi-Label Classification Algorithm for Adaptive Heterogeneous Classifier Group by Meng Han, Shurong Yang, Hongxin Wu, Jian Ding

Subjects: “…multi-label classification…”
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Video inter-frame tampering detection algorithm fusing multiple features by Hui XIAO, Bin WENG, Tianqiang HUANG, Han PU, Zehui HUANG

Subjects: “…video tamper detection…”
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Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose. by Jia Liu, Jinglei Zhang, Shaoqi Zhang, Kaiwei Li, Xiang Li, Shuo Zhang, Hang Gu, Zhen Chen, Chao Liu, Nan Zhang, Tong Sun

“…For this issue, we proposed a new sensor array optimization algorithm named Interfered Feature Elimination coupled with Feature Group Selection (IFE-FGS). In this method, the IFE algorithm first removed the bad sensor features; then the FGS algorithm determined the optimized sensor combination by gradually selecting the features in groups. …”
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Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…In comparison to the various state-of-the-art classifiers, the CSO method was applied to the NSL-KDD dataset and the ROSPaCe dataset for the detection of the attacks. In the proposed work, we have used a random forest technique to perform feature selection (FS) to improve the effectiveness and efficiency of intrusion detection. …”
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Comparison of different classification of metabolic syndrome in the Kyrgyz ethnic group by Ch. B. Moldokeeva, O. S. Lunegova, A. S. Kerimkulova, A. E. Mirrakhimov, S. S. Abilova, A. A. Bairamukova, Yu. V. Zalesskaya, E. M. Mirrakhimov

“…Goal: Comparison of different classification of metabolic syndrome (MS) in Kyrgyz ethnic group. …”
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Group feature calibration for sound event detection by Yanzhen Ren, Wuyang Liu, Chenyu Liu, Tingting Zhu

“…Abstract Sound Event Detection (SED) is a pivotal task in audio signal processing with widespread applications, requiring the classification and temporal localization of sound events. …”
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Effective and Reliable Malware Group Classification for a Massive Malware Environment by Taejin Lee, Jin Kwak

“…This paper proposes a scheme for the detection and group classification of malware, some measures to improve the dependability of classification using the local clustering coefficient, and the technique for selecting and managing the leading malware for each group to classify them cost-effectively in a massive malware environment. …”
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Phytoplankton group classification by integrating trait information and observed environmental thresholds by Hoang Vuong Dang, Kermode Stephanie, Peisheng Huang, Cayelan C. Carey, Matthew R. Hipsey

“…Third, we applied K-prototype clustering for group classification based on the identified thresholds and associated traits. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…Finally, social group optimization (SGO) optimally adjusts the ensemble classifiers’ hyperparameter values, resulting in better classification performance. …”
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Explainable handcrafted features for mitotic event detection and classification by Panason Manorost, Thomas Deckers, Veerle Bloemen, Jean Marie Aerts

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Transformer-based ECG classification for early detection of cardiac arrhythmias by Sunnia Ikram, Amna Ikram, Harvinder Singh, Malik Daler Ali Awan, Sajid Naveed, Isabel De la Torre Díez, Henry Fabian Gongora, Thania Candelaria Chio Montero

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Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network by Zhenzhe Qin, Yongbo Li, Xiaoying Song, Li Chai

“…For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). …”
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An improved electrocardiogram arrhythmia classification performance with feature optimization by Annisa Darmawahyuni, Siti Nurmaini, Bambang Tutuko, Muhammad Naufal Rachmatullah, Firdaus Firdaus, Ade Iriani Sapitri, Anggun Islami, Jordan Marcelino, Rendy Isdwanta, Muhammad Ikhwan Perwira

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Problem of selection of suitable geosynthetics for the strengthening of subgrade by Elżbieta Szafranko

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Group Abnormal Behaviour Detection Algorithm Based on Global Optical Flow by Yu Hao, Ying Liu, Jiulun Fan, Zhijie Xu

“…The network uses two network branches to learn spatial dimension information and temporal dimension information, respectively, and uses short- and long-time neural network to model the dependency relationship between long-time video frames, so as to obtain the final behaviour classification results. Simulation test results show that the proposed method can achieve good recognition effect on multiple datasets, and the performance of abnormal behaviour detection can be significantly improved by using interframe motion information.…”
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Cells Grouping Detection and Confusing Labels Correction on Cervical Pathology Images by Wenbo Pang, Yi Ma, Huiyan Jiang, Qiming Yu

“…Specifically, we utilize clinical prior knowledge to break down the detection task into multiple sub-tasks for cell grouping detection, aiming to more effectively learn the specific structure of cells. …”
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Artificial Intelligence Classification for Detecting and Grading Lumbar Intervertebral Disc Degeneration by Wongthawat Liawrungrueang, Watcharaporn Cholamjiak, Peem Sarasombath, Khanathip Jitpakdee, Vit Kotheeranurak

“…Conclusions: The AI-based classification model exhibits high accuracy, sensitivity, and specificity in detecting and grading lumbar IDD using the Pfirrmann grading. …”
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A complete benchmark for polyp detection, segmentation and classification in colonoscopy images by Yael Tudela, Mireia Majó, Neil de la Fuente, Adrian Galdran, Adrian Krenzer, Frank Puppe, Amine Yamlahi, Thuy Nuong Tran, Bogdan J. Matuszewski, Kerr Fitzgerald, Cheng Bian, Junwen Pan, Shijle Liu, Gloria Fernández-Esparrach, Aymeric Histace, Jorge Bernal

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Gas Detection and Classification Using Neural Network Based Gas Sensors by Munaf Ismail, Sri Arttini Dwi Prasetyowati

“…For this experiment, ANN is used as a liquid classification in grouping alcoholic and non-alcoholic liquids. …”
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Metric-Based Few-Shot Learning With Triplet Selection for Adaptive GNSS Interference Classification by Felix Ott, Lucas Heublein, Tobias Feigl, Alexander Rugamer, Christopher Mutschler

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