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Time2Vec transformer: a time series approach for gas detection in seismic data., , , , , , , , , и . SAC, стр. 66-72. ACM, (2022)Detection and Delimitation of Natural Gas in Seismic Images using MLP-Mixer and U-Net., , , , , , и . ICEIS (1), стр. 578-585. SCITEPRESS, (2022)Heart segmentation in planning CT using 2.5D U-Net++ with attention gate., , , , , , , , и . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (3): 317-325 (мая 2023)Meta-Data Construction for Selection of Breast Tissue Biopsy Slides Image Classifier to Identify Ductal Carcinoma., , и . BRACIS, стр. 729-734. IEEE, (2019)Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization., , , , , , , , , и 7 other автор(ы). Eng. Appl. Artif. Intell., (2021)EfficientDeepLab for Automated Trachea Segmentation on Medical Images., , , , и . BRACIS (2), том 14196 из Lecture Notes in Computer Science, стр. 154-166. Springer, (2023)A deep learning method with residual blocks for automatic spinal cord segmentation in planning CT., , , , и . Biomed. Signal Process. Control., 71 (Part): 103074 (2022)Deployment of a Machine Learning System for Predicting Lawsuits Against Power Companies: Lessons Learned from an Agile Testing Experience for Improving Software Quality., , , , , , , и . SBQS, стр. 30. ACM, (2020)Image-Based Electric Consumption Recognition via Multi-Task Learning., , , , , , , и . BRACIS, стр. 419-424. IEEE, (2019)Esophagus segmentation from planning CT images using an atlas-based deep learning approach., , , , и . Comput. Methods Programs Biomed., (2020)