PUB - Publikationen an der Universität Bielefeld

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• [10]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2989164

  Velioglu, R., Chan, R.K.-W., & Hammer, B., 2024. FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation. In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE International Joint Conference on Neural Networks (IJCNN). New York: Institute of Electrical and Electronics Engineers (IEEE).

  PUB | DOI | WoS | arXiv
   
• [9]
  

  2024 | Preprint | PUB-ID: 2999454

  Velioglu, R., et al., 2024. TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models. arXiv:2411.18350.

  PUB | arXiv
   
• [8]
  

  2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2967296

  Velioglu, R., et al., 2022. Explainable Artificial Intelligence for Improved Modeling of Processes. In H. Yin, D. Camacho, & P. Tino, eds. Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings. Lecture Notes in Computer Science. no.13756 Cham: Springer International Publishing, pp. 313-325.

  PUB | DOI
   
• [7]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982067

  Hermes, L., et al., 2022. A Graph-based U-Net Model for Predicting Traffic in unseen Cities. In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-8.

  PUB | DOI
   
• [6]
  

  2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2961319

  Ozdemir, O., et al., 2022. A comparative study of neural machine translation models for Turkish language. Journal of Intelligent & Fuzzy Systems , 42(3), p 2103-2113.

  PUB | DOI | WoS
   
• [5]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747

  Artelt, A., et al., 2021. Evaluating Robustness of Counterfactual Explanations. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ: IEEE, pp. 01-09.

  PUB | DOI
   
• [4]
  

  2021 | Dissertation | PUB-ID: 2989295

  Velioglu, R., 2021. Detecting Hate Speech In Multimodal Memes Using Vision-Language Models,

  PUB | PDF
   
• [3]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982064

  Kiela, D., et al., 2021. The Hateful Memes Challenge: Competition Report. In H. J. Escalante & K. Hofmann, eds. Proceedings of the NeurIPS 2020 Competition and Demonstration Track. Proceedings of Machine Learning Research. no.133 PMLR, pp. 344-360.

  PUB
   
• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2965471

  Velioglu, R., & Rose, J., 2020. Detecting Hate Speech in Memes Using Multimodal Deep Learning Approaches: Prize-winning solution to Hateful Memes Challenge. In arXiv:2012.12975.

  PUB | arXiv
   
• [1]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2965472

  Velioglu, R., Yildiz, T., & Yildirim, S., 2018. Sentiment Analysis Using Learning Approaches Over Emojis for Turkish Tweets. In 2018 3rd International Conference on Computer Science and Engineering (UBMK). IEEE, pp. 303-307.

  PUB | DOI