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  1. 2041

    Delving into Underwater Image Utility: Benchmark Dataset and Prediction Model by Jiapeng Liu, Yi Liu, Qiuping Jiang

    Published 2025-05-01
    “…On the other hand, based on this newly constructed OD-UIUA dataset, we train a deep UIUA network (DeepUIUA) that can automatically and accurately predict UIUS. To the best of our knowledge, this is the first benchmark dataset for UIUA and also the first model focusing on the specific UIUA problem. …”
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  2. 2042

    Coal and gas outburst prediction based on data augmentation and neuroevolution. by Wenbing Shi, Ji Huang, Gaoming Yang, Shuzhi Su, Shexiang Jiang

    Published 2025-01-01
    “…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. …”
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  3. 2043

    Multiclass Sparse Bayesian Regression for fMRI-Based Prediction by Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion

    Published 2011-01-01
    “…However, it relies on a prediction function that is plagued by the curse of dimensionality, as there are far more features (voxels) than samples (images), and dimension reduction is thus a mandatory step. …”
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  4. 2044

    Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

    Published 2025-01-01
    “…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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  5. 2045

    Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

    Published 2024-09-01
    “…The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. …”
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  6. 2046

    Co-folding, the future of docking – prediction of allosteric and orthosteric ligands by Eva Nittinger, Özge Yoluk, Alessandro Tibo, Gustav Olanders, Christian Tyrchan

    Published 2025-12-01
    “…Recently, computational biology has seen a breakthrough with deep learning algorithms capable of predicting protein structures based on amino acid sequences. …”
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  7. 2047

    Development of time to event prediction models using federated learning by Rasmus Rask Kragh Jørgensen, Jonas Faartoft Jensen, Tarec El-Galaly, Martin Bøgsted, Rasmus Froberg Brøndum, Mikkel Runason Simonsen, Lasse Hjort Jakobsen

    Published 2025-05-01
    “…Method We propose two methods for training time-to-event prediction models based on distributed data, relying on FL algorithms, for time-to-event prediction models. …”
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  8. 2048

    Predicting the generalization of computer aided detection (CADe) models for colonoscopy by Joel Shor, Carson McNeil, Yotam Intrator, Joseph R. Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

    Published 2024-11-01
    “…We show that a "Masked Siamese Network" (MSN), trained to predict masked out regions of polyp images without labels, can predict the performance of Computer Aided Detection (CADe) of polyps on colonoscopies, without labels. …”
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  9. 2049

    Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

    Published 2025-07-01
    “…(Research purpose) The aim of this study is to analyze data structures and compare machine learning and deep learning algorithms used in used in crop yield prediction. (Materials and methods) Using a convergent approach and applying methods of cognitive and semantic analysis, the authors examined the subject area of artificial intelligence applications in crop yield prediction. …”
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  10. 2050

    Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals by Sowmya Vijayakumar, Ronan Flynn, Peter Corcoran, Niall Murray

    Published 2025-01-01
    “…We compare the performances of several machine learning (ML) and deep learning (DL) models in predicting QoE subjective scores from electrocardiograms and respiration signals. …”
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  11. 2051

    A Hybrid Learning Framework for Enhancing Bridge Damage Prediction by Amal Abdulbaqi Maryoosh, Saeid Pashazadeh, Pedram Salehpour

    Published 2025-04-01
    “…The proposed approach combines pixel-based feature method local binary pattern (LBP) with the mid-level feature bag of visual words (BoVW) for feature extraction, followed by the Apriori algorithm for dimensionality reduction and optimal feature selection. …”
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  12. 2052

    Composite Noise Reduction Method for Internal Leakage Acoustic Emission Signal of Safety Valve Based on IWTD-IVMD Algorithm by Shuxun Li, Xiaoqi Meng, Jianjun Hou, Kang Yuan, Xiaoya Wen

    Published 2025-07-01
    “…Therefore, the IWTD-IVMD composite noise reduction method can extract more main features out of the measured spring full-open safety valve internal leakage acoustic emission signals, and has a good noise reduction effect. …”
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  13. 2053
  14. 2054

    In Situ Calculation of Spaceflight Magnetometer Coupling Coefficients for Interference Removal Using the Reduction Algorithm for Magnetometer Electromagnetic Noise (RAMEN) by Alex P. Hoffmann, Mark B. Moldwin

    Published 2025-04-01
    “…We propose a novel method for in situ calculation of the gradiometric coupling coefficients, called the Reduction Algorithm for Magnetometer Electromagnetic Noise (RAMEN). …”
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  15. 2055
  16. 2056
  17. 2057

    Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm by Tung Tran The, Dieu Vo Ngoc, Nguyen Tran Anh

    Published 2020-01-01
    “…This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. …”
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  18. 2058
  19. 2059
  20. 2060

    A Low-Complexity Block Diagonalization Algorithm for MU-MIMO Two-Way Relay Systems with Complex Lattice Reduction by Lin Xiao, Shengen Liu, Dingcheng Yang

    Published 2015-06-01
    “…To reduce the complexity of proposed precoding scheme, we employ the QR decomposition and complex lattice reduction (CLR) transform to replace the two times singular value decomposition (SVD) of conventional BD-based precoding algorithm by introducing a combined channel inversion to eliminate the multiple users interference (MUI). …”
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