Chenyang Shen

Research output

Research output per year 2013 2018 2019 2020 2021 2022 2023 2023

• 50 Article
• 9 Conference contribution
• 1 Chapter
• 1 Comment/debate
• 1 More
  • 1 Review article

Research output per year

Research output per year

Search results

• 2020

  A Neural Network Approach for Image Reconstruction from a Single X-Ray Projection

  Rouf, S., Shen, C., Cao, Y., Davis, C., Jia, X. & Lou, Y., 2020, Medical Image Understanding and Analysis - 23rd Conference, MIUA 2019, Proceedings. Zheng, Y., Williams, B. M. & Chen, K. (eds.). Springer, p. 208-219 12 p. (Communications in Computer and Information Science; vol. 1065 CCIS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Image Reconstruction 100%
  • Image reconstruction 80%
  • Neural Networks 72%
  • X rays 70%
  • Principal component analysis 58%

• Fast and Robust Compression of Deep Convolutional Neural Networks

  Wen, J., Yang, L. & Shen, C., 2020, Artificial Neural Networks and Machine Learning – ICANN 2020 - 29th International Conference on Artificial Neural Networks, Proceedings. Farkaš, I., Masulli, P. & Wermter, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 52-63 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12397 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Compression 100%
  • Tensor Decomposition 95%
  • Deep neural networks 95%
  • Neural Networks 92%
  • Convolutional neural networks 89%
  2 Scopus citations
• 2019

  Generating Pareto Optimal Dose Distributions for Radiation Therapy Treatment Planning

  Nguyen, D., Barkousaraie, A. S., Shen, C., Jia, X. & Jiang, S., 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 59-67 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11769 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Radiation Therapy 100%
  • Radiotherapy 80%
  • Dose 71%
  • Planning 66%
  • Target 31%
  17 Scopus citations

• Heterogeneous transfer clustering for partial Co-occurrence data

  Ye, X., Yang, L., Hu, Q., Shen, C., Jing, L. & Du, Z., Nov 2019, Proceedings - IEEE 31st International Conference on Tools with Artificial Intelligence, ICTAI 2019. IEEE Computer Society, p. 1042-1049 8 p. 8995324. (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; vol. 2019-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Redundancy 100%
  • Experiments 41%

• Low-dose CT reconstruction assisted by a global CT image manifold prior

  Shen, C., Ma, G. & Jia, X., 2019, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. Matej, S. & Metzler, S. D. (eds.). SPIE, 1107205. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11072).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Computed Tomography 100%
  • Dose 76%
  • Tomography 67%
  • tomography 55%
  • Error 52%
  3 Scopus citations

• Quality-guided deep reinforcement learning for parameter tuning in iterative CT reconstruction

  Shen, C., Tsai, M. Y., Gonzalez, Y., Chen, L., Jiang, S. B. & Jia, X., 2019, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. Matej, S. & Metzler, S. D. (eds.). SPIE, 1107203. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11072).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Reinforcement Learning 100%
  • Parameter Tuning 81%
  • learning 72%
  • reinforcement 70%
  • Reinforcement learning 66%
  4 Scopus citations

• Transfer Learning for Driving Pattern Recognition

  Li, M., Yang, L., Hu, Q., Shen, C. & Du, Z., 2019, PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Nayak, A. C. & Sharma, A. (eds.). Springer Verlag, p. 52-65 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11671 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Transfer Learning 100%
  • Transfer learning 63%
  • Pattern Recognition 60%
  • Pattern recognition 46%
  • Labeled data 20%
• 2014

  A tensor-based Markov chain method for module identification from multiple networks

  Shen, C., Zhang, S. & Ng, M. K., Dec 17 2014, International Conference on Systems Biology, ISB. Chen, L., Zhang, X-S., Wu, L-Y. & Wang, Y. (eds.). IEEE Computer Society, p. 49-58 10 p. 6990431

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Markov Chains 100%
  • Tensors 71%
  • Markov chains 69%
  • Genes 68%
  • Markov chain 59%
  1 Scopus citations
• 2013

  Sparse-MIML: A sparsity-based multi-instance multi-learning algorithm

  Shen, C., Jing, L. & Ng, M. K., Oct 8 2013, Energy Minimization Methods in Computer Vision and Pattern Recognition - 9th International Conference, EMMCVPR 2013, Proceedings. p. 294-306 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8081 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Learning Algorithm 100%
  • Sparsity 88%
  • Labels 71%
  • Learning algorithms 70%
  • Object 57%
  4 Scopus citations