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Conference Papers on "Multimedia Analysis and Machine Learning" at the Chair of Prof. Dr. Christoph Meinel

Here you can find all our peer-reviewed conference papers about deep learning, machine learning, multimedia analysis and indexing:

[ 2024 ] [ 2023 ] [ 2022 ] [ 2021 ] [ 2020 ] [ 2019 ] [ 2018 ] [ 2017 ] [ 2016 ] [ 2015 ] [ 2014 ] [ 2013 ] [ 2012 ] [ 2011 ]

2024 [ nach oben ]

  • 1.
    Otholt, J., Meinel, C., Yang, H.: Guided Cluster Aggregation: A Hierarchical Approach to Generalized Category Discovery. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024). pp. 2618–2627 (2024).
     

2023 [ nach oben ]

  • 1.
    Simsek, F., Pfitzmann, B., Raetz, H., Otholt, J., Yang, H., Meinel, C.: DocLangID: Improving Few-Shot Training to Identify the Language of Historical Documents. Proceedings of the 7th International Workshop on Historical Document Imaging and Processing. pp. 103–108. ACM (2023).
     

2022 [ nach oben ]

  • 1.
    Bartz, C., Raetz, H., Otholt, J., Meinel, C., Yang, H.: Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data. 2022 26th International Conference on Pattern Recognition (ICPR). pp. 3878–3884 (2022).
     
  • 2.
    Li, ziyun, Otholt, J., Dai, B., Hu, D., Meinel, C., Yang, H.: A Closer Look at Novel Class Discovery from the Labeled Set. Workshop on Distribution Shifts: Connecting Methods and Applications, NeurIPS 2022 (2022).
     
  • 3.
    Li, Z., Wang, X., Hu, D., Robertson, N.M., Clifton, D.A., Meinel, C., Yang, H.: Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge. Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022 (2022).
     
  • 4.
    Bartz, C., Raetz, H., Otholt, J., Meinel, C., Yang, H.: Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data. 2022 26th International Conference on Pattern Recognition (ICPR). pp. 3878–3884 (2022).
     

2021 [ nach oben ]

  • 1.
    Guo, N., Bethge, J., Yang, H., Zhong, K., Ning, X., Meinel, C., Wang, Y.: Boolnet: Minimizing the Energy Consumption of Binary Neural Networks. arXiv preprint arXiv:2106.06991. (2021).
     
  • 2.
    Hilscher, M., Tjabben, H., Rätz, H., Semmo, A., Besanc con, L., Döllner, J., Trapp, M.: Service-based Analysis and Abstraction for Content Moderation of Digital Images. Graphics Interface 2021. , Vancouver, Canada (2021).
     
  • 3.
    Von Thienen, J., Borchart, K., Jaschek, C., Krebs, E., Hildebrand, J., Rätz, H., Meinel, C.: Leveraging Video Games to Improve IT-Solutions for Remote Work. 2021 IEEE Conference on Games (CoG). pp. 01–08 (2021).
     
  • 4.
    Bartz, C., Rätz, H., Meinel, C.: Handwriting Classification for the Analysis of Art-Historical Documents. In: Del Bimbo, A., Cucchiara, R., Sclaroff, S., Farinella, G.M., Mei, T., Bertini, M., Escalante, H.J., and Vezzani, R. (eds.) Pattern Recognition. ICPR International Workshops and Challenges. pp. 562–576. Springer International Publishing, Cham (2021).
     
  • 5.
    Hu, T., Yang, H., Meinel, C.: Denoising AutoEncoder Based Delete and Generate Approach for Text Style Transfer. International Conference on Artificial Neural Networks. pp. 41–52. Springer, on-line (2021).
     
  • MeliusNet: An Improved Ne... - Download
    6.
    Bethge, J., Bartz, C., Yang, H., Chen, Y., Meinel, C.: MeliusNet: An Improved Network Architecture for Binary Neural Networks. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2021).
     
  • 7.
    Hu, T., Meinel, C.: Masked Hard Coverage Mechanism on Pointer-generator Network for Natural Language Generation. ICAART (2). pp. 1177–1183 (2021).
     
  • 8.
    Yang, H., Shen, Z., Zhao, Y.: AsymmNet: Towards ultralight convolution neural networks using asymmetrical bottlenecks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2339–2348 (2021).
     

2020 [ nach oben ]

  • 1.
    Bethge, J., Bartz, C., Yang, H., Meinel, C.: BMXNet 2: An Open Source Framework for Low-bit Networks-Reproducing, Understanding, Designing and Showcasing. Proceedings of the 28th ACM International Conference on Multimedia. pp. 4469–4472 (2020).
     
  • 2.
    Mordido, G., Yang, H., Meinel, C.: microbatchgan: Stimulating diversity with multi-adversarial discrimination. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 3061–3070 (2020).
     
  • 3.
    Bartz, C., Seidel, L., Nguyen, D.-H., Bethge, J., Yang, H., Meinel, C.: Synthetic Data for the Analysis of Archival Documents: Handwriting Determination. 2020 Digital Image Computing: Techniques and Applications (DICTA). pp. 1–8. IEEE (2020).
     
  • 4.
    Bartz, C., Bethge, J., Yang, H., Meinel, C.: One model to reconstruct them all: A novel way to use the stochastic noise in StyleGAN. The British Machine Vision Conference (BMVC) (2020).
     
  • 5.
    Sauder, J., Hu, T., Che, X., Mordido, G., Yang, H., Meinel, C.: Best student forcing: A simple training mechanism in adversarial language generation. Proceedings of the 12th Language Resources and Evaluation Conference. pp. 4680–4688 (2020).
     
  • 6.
    Jain, N., Bartz, C., Bredow, T., Metzenthin, E., Otholt, J., Krestel, R.: Semantic Analysis of Cultural Heritage Data: Aligning Paintings and Descriptions in Art-Historic Collections. International Workshop on Fine Art Pattern Extraction and Recognition in conjunction with the 25th International Conference on Pattern Recognition (ICPR 2020) (2020).
     
  • 7.
    Rezaei, M., Yang, H., Meinel, C.: Recurrent generative adversarial network for learning imbalanced medical image semantic segmentation. Multimedia Tools and Applications. 79, 15329–15348 (2020).
     
  • 8.
    Hu, T., Meinel, C.: Text generation in discrete space. International Conference on Artificial Neural Networks. pp. 721–732. Springer (2020).
     
  • 9.
    Hu, T., Meinel, C.: An Investigation of Fine-tuning Pre-trained Model for MR-to-Text Generation. 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). pp. 1006–1009. IEEE (2020).
     

2019 [ nach oben ]

  • 1.
    Bethge, J., Yang, H., Meinel, C.: Training Accurate Binary Neural Networks from Scratch. 2019 26th IEEE International Conference on Image Processing (ICIP) (2019).
     
  • 2.
    Rezaei, M., Yang, H., Harmuth, K., Meinel, C.: Conditional generative adversarial refinement networks for unbalanced medical image semantic segmentation. 2019 IEEE winter conference on applications of computer vision (WACV). pp. 1836–1845. IEEE (2019).
     
  • 3.
    Bethge, J., Yang, H., Bornstein, M., Meinel, C.: BinaryDenseNet: Developing an Architecture for Binary Neural Networks. The IEEE International Conference on Computer Vision (ICCV) Workshops (2019).
     

2018 [ nach oben ]

  • 1.
    Mordido, G., Yang, H., Meinel, C.: Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators. KDD2018 (2018).
     
  • 2.
    Bartz, C., Yang, H., Meinel, C.: SEE: towards semi-supervised end-to-end scene text recognition. Proceedings of the AAAI Conference on Artificial Intelligence (2018).
     
  • 3.
    Bartz, C., Yang, H., Bethge, J., Meinel, C.: Loans: Weakly supervised object detection with localizer assessor networks. Asian Conference on Computer Vision. pp. 341–356. Springer (2018).
     
  • 4.
    Rezaei, M., Yang, H., Meinel, C.: voxel-GAN: adversarial framework for learning imbalanced brain tumor segmentation. International MICCAI Brainlesion Workshop. pp. 321–333. Springer (2018).
     
  • 5.
    Rezaei, M., Yang, H., Meinel, C.: Instance tumor segmentation using multitask convolutional neural network. 2018 International Joint Conference on Neural Networks (IJCNN). pp. 1–8. IEEE (2018).
     
  • 6.
    Rezaei, M., Yang, H., Meinel, C.: Whole heart and great vessel segmentation with context-aware of generative adversarial networks. Bildverarbeitung für die Medizin 2018. pp. 353–358. Springer (2018).
     

2017 [ nach oben ]

  • 1.
    Bartz, C., Herold, T., Yang, H., Meinel, C.: Language identification using deep convolutional recurrent neural networks. International conference on neural information processing. pp. 880–889. Springer (2017).
     
  • 2.
    Rezaei, M., Yang, H., Meinel, C.: Deep Neural Network with l2-norm Unit for Brain Lesions Detection. International Conference on Neural Information Processing. Springer (2017).
     
  • 3.
    Yang, H., Fritzsche, M., Bartz, C., Meinel, C.: BMXNet: An Open-Source Binary Neural Network Implementation Based on MXNet. Proceedings of the 2017 ACM on Multimedia Conference. ACM, New York, NY, USA (2017).
     
  • 4.
    Rezaei, M., Harmuth, K., Gierke, W., Kellermeier, T., Fischer, M., Yang, H., Meinel, C.: A conditional adversarial network for semantic segmentation of brain tumor. International MICCAI Brainlesion Workshop. pp. 241–252. Springer (2017).
     
  • 5.
    Yang, H., Fritzsche, M., Bartz, C., Meinel, C.: Bmxnet: An open-source binary neural network implementation based on mxnet. Proceedings of the 25th ACM international conference on Multimedia (2017).
     
  • 6.
    Che, X., Ring, N., Raschkowski, W., Yang, H., Meinel, C.: Traversal-free word vector evaluation in analogy space. Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP. pp. 11–15 (2017).
     
  • 7.
    Rezaei, M., Yang, H., Meinel, C.: Deep neural network with l2-norm unit for brain lesions detection. International Conference on Neural Information Processing. pp. 798–807. Springer (2017).
     
  • 8.
    Che, X., Luo, S., Yang, H., Meinel, C.: Automatic lecture subtitle generation and how it helps. 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT). pp. 34–38. IEEE (2017).
     
  • 9.
    Bethge, J., Hahn, S., Döllner, J.: Improving Layout Quality by Mixing Treemap-Layouts Based on Data-Change Characteristics. In: Hullin, M., Klein, R., Schultz, T., and Yao, A. (eds.) Vision, Modeling & Visualization. The Eurographics Association (2017).
     
  • 10.
    Hahn, S., Bethge, J., Döllner, J.: Relative Direction Change: A Topology-based Metric for Layout Stability in Treemaps. Proceedings of the 8th International Conference of Information Visualization Theory and Applications (IVAPP 2017) (2017).
     
  • 11.
    Bartz, C., Herold, T., Yang, H., Meinel, C.: Language Identification Using Deep Convolutional Recurrent Neural Networks. International Conference on Neural Information Processing. Springer (2017).
     

2016 [ nach oben ]

  • 1.
    Che, X., Wang, C., Yang, H., Meinel, C.: Punctuation prediction for unsegmented transcript based on word vector. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). pp. 654–658 (2016).
     
  • 2.
    Wang, C., Yang, H., Bartz, C., Meinel, C.: Image captioning with deep bidirectional LSTMs. Proceedings of the 24th ACM international conference on Multimedia. pp. 988–997 (2016).
     
  • 3.
    Rantzsch, H., Yang, H., Meinel, C.: Signature embedding: Writer independent offline signature verification with deep metric learning. International symposium on visual computing. pp. 616–625. Springer (2016).
     
  • 4.
    Yang, H., Wang, C., Bartz, C., Meinel, C.: SceneTextReg: a real-time video OCR system. Proceedings of the 24th ACM international conference on Multimedia (2016).
     
  • 5.
    Che, X., Luo, S., Yang, H., Meinel, C.: Sentence Boundary Detection Based on Parallel Lexical and Acoustic Models. Presented at the (2016).
     
  • 6.
    Yang, H., Wang, C., Bartz, C., Meinel, C.: SceneTextReg: A Real-Time Video OCR System. Proceedings of the 2016 ACM on Multimedia Conference. pp. 698–700. ACM, Amsterdam, The Netherlands (2016).
     
  • 7.
    Wang, C., Yang, H., Bartz, C., Meinel, C.: Image Captioning with Deep Bidirectional LSTMs. Proceedings of the 2016 ACM on Multimedia Conference. pp. 988–997. ACM, Amsterdam, The Netherlands (2016).
     
  • 8.
    Wang, C., Yang, H., Meinel, C.: Exploring multimodal video representation for action recognition. 2016 International Joint Conference on Neural Networks (IJCNN). pp. 1924–1931 (2016).
     
  • 9.
    Rantzsch, H., Yang, H., Meinel, C.: Signature Embedding: Writer Independent Offline Signature Verification with Deep Metric Learning. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Porikli, F., Skaff, S., Entezari, A., Min, J., Iwai, D., Sadagic, A., Scheidegger, C., and Isenberg, T. (eds.) Advances in Visual Computing: 12th International Symposium, ISVC 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part II. pp. 616–625. Springer International Publishing, Cham (2016).
     
  • 10.
    Wang, C., Yang, H., Meinel, C.: Exploring multimodal video representation for action recognition. 2016 International Joint Conference on Neural Networks (IJCNN). pp. 1924–1931. IEEE (2016).
     

2015 [ nach oben ]

  • 1.
    Quehl, B., Yang, H., Sack, H.: Improving text recognition by distinguishing scene and overlay text. , SPIE (2015).
     
  • 2.
    Wang, C., Yang, H., Che, X., Meinel, C.: Concept-based multimodal learning for topic generation. International Conference on Multimedia Modeling. pp. 385–395. Springer (2015).
     
  • 3.
    Luo, S., Yang, H., Meinel, C.: Reward-based Intermittent Reinforcement in Gamification for E-learning. Presented at the (2015).
     
  • 4.
    Yang, H., Wang, C., Che, X., Luo, S., Meinel, C.: An improved system for real-time scene text recognition. Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (2015).
     
  • 5.
    Wang, C., Yang, H., Meinel, C.: Deep semantic mapping for cross-modal retrieval. 2015 IEEE 27th International conference on tools with artificial intelligence (ICTAI). pp. 234–241. IEEE (2015).
     
  • 6.
    Che, X., Yang, H., Meinel, C.: Adaptive e-lecture video outline extraction based on slides analysis. International Conference on Web-Based Learning. pp. 59–68. Springer (2015).
     

2014 [ nach oben ]

  • 1.
    Yang, H., Quehl, B., Sack, H.: A framework for improved video text detection and recognition. Multimedia tools and applications. 69, 217–245 (2014).
     

2013 [ nach oben ]

  • 1.
    Yang, H., Grünewald, F., Bauer, M., Meinel, C.: Lecture video browsing using multimodal information resources. International Conference on Web-Based Learning. pp. 204–213. Springer (2013).
     
  • 2.
    Che, X., Yang, H., Meinel, C.: Lecture video segmentation by automatically analyzing the synchronized slides. Proceedings of the 21st ACM international conference on Multimedia. pp. 345–348 (2013).
     
  • 3.
    Grünewald, F., Yang, H., Meinel, C.: Evaluating the digital manuscript functionality--User testing for lecture video annotation features. International Conference on Web-Based Learning. pp. 214–223. Springer (2013).
     
  • 4.
    Yang, H., Grünewald, F., Bauer, M., Meinel, C.: Lecture Video Browsing Using Multimodal Information Resources. 12th International Conference on Web-based Learning (ICWL). pp. 204–213. Springer Berlin Heidelberg (2013).
     

2012 [ nach oben ]

  • 1.
    Yang, H., Gruenewald, F., Meinel, C.: Automated extraction of lecture outlines from lecture videos. Presented at the (2012).
     
  • 2.
    Yang, H., Quehl, B., Sack, H.: Text detection in video images using adaptive edge detection and stroke width verification. 2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP). pp. 9–12. IEEE (2012).
     
  • 3.
    Yang, H., Oehlke, C., Meinel, C.: An automated analysis and indexing framework for lecture video portal. International Conference on Web-Based Learning. pp. 285–294. Springer (2012).
     
  • 4.
    Hentschel, C., Hercher, J., Knuth, M., Osterhoff, J., Quehl, B., Sack, H., Steinmetz, N., Waitelonis, J., Yang, H.: Open Up Cultural Heritage in Video Archives with Mediaglobe. Proceedings of the 12th International Conference on Innovative Internet Community Services (I2CS 2012) (2012).
     

2011 [ nach oben ]

  • 1.
    Yang, H., Oehlke, C., Meinel, C.: German speech recognition: A solution for the analysis and processing of lecture recordings. 2011 10th IEEE/ACIS International Conference on Computer and Information Science. pp. 201–206. IEEE (2011).
     
  • 2.
    Yang, H., Siebert, M., Luhne, P., Sack, H., Meinel, C.: Lecture video indexing and analysis using video ocr technology. 2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems. pp. 54–61. IEEE (2011).
     

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