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Results: 17
Number of items: 17
  • Open Access
    Katona, Z., Mohammadi Ziabari, S. S., & Karimi Nejadasl, F. (2025). MARINE: A Computer Vision Model for Detecting Rare Predator-Prey Interactions in Animal Videos. In A. Dasgupta, R. U. Kiran, R. El Shawi, S. Srirama, & M. Adhikari (Eds.), Big Data and Artificial Intelligence: 12th International Conference, BDA 2024, Hyderabad, India, December 17–20, 2024 : proceedings (pp. 183–199). (Lecture Notes in Computer Science; Vol. 15526). Springer. https://doi.org/10.1007/978-3-031-81821-9_11
  • Open Access
    Ashtar, D., Mohammadi Ziabari, S., & Alsahag, A. M. M. (2025). Hybrid Forecasting for Sustainable Electricity Demand in The Netherlands Using SARIMAX, SARIMAX-LSTM, and Sequence-to-Sequence Deep Learning Models. Sustainability, 17(16), Article 7192. https://doi.org/10.3390/su17167192
  • Open Access
    Coolwijk, S., Mohammadi Ziabari, S. S., & Angileri, F. (2025). Vision Transformer Approach to Customer Churn Prediction Radar Chart Image Classification for Non-subscription Based E-commerce. In P. Delir Haghighi, M. Greguš, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence: 26th International Conference, iiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024 : proceedings (Vol. II, pp. 75–80). (Lecture Notes in Computer Science; Vol. 15343). Springer. https://doi.org/10.1007/978-3-031-78093-6_6
  • Open Access
    Anwar, K., & Mohammadi Ziabari, S. S. (2025). Attention to the Branches: A Comparative Analysis of FairMOT with Transformers on Fish Dataset. In C. Sombattheera, P. Weng, & J. Pang (Eds.), Multi-disciplinary Trends in Artificial Intelligence: 17th International Conference, MIWAI 2024, Pattaya, Thailand, November 11–15, 2024 : proceedings (Vol. I, pp. 64–76). (Lecture Notes in Computer Science; Vol. 15431), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-981-96-0692-4_6
  • Open Access
    van de Sande, S. N. P., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2024). Enhancing the Predictability of Wintertime Energy Demand in The Netherlands Using Ensemble Model Prophet-LSTM. Processes, 12(11), Article 2519. https://doi.org/10.3390/pr12112519
  • Open Access
    Chikhi, A., Mohammadi Ziabari, S. S., & van Essen, J. W. (2023). A Comparative Study of Traditional, Ensemble and Neural Network-Based Natural Language Processing Algorithms. Journal of Risk and Financial Management, 16(7), Article 327. https://doi.org/10.3390/jrfm16070327
  • Open Access
    De Bosscher, B. C. D., Mohammadi Ziabari, S. S., & Sharpanskykh, A. (2023). A comprehensive study of agent-based airport terminal operations using surrogate modeling and simulation. Simulation Modelling Practice and Theory, 128, Article 102811. https://doi.org/10.1016/j.simpat.2023.102811
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