Research output per year
Research output per year
Fingerprint
Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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CatchBackdoor: Backdoor Detection via Critical Trojan Neural Path Fuzzing
Jin, H., Chen, R., Chen, J., Zheng, H., Zhang, Y. & Wang, H., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer, p. 90-106 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15105 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models
Chen, R., Jin, H., Liu, Y., Chen, J., Wang, H. & Sun, L., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer, p. 126-142 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15121 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Simple Unsupervised Knowledge Distillation With Space Similarity
Singh, A. & Wang, H., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer, p. 147-164 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15060 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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ZooPFL: Exploring Black-Box Foundation Models for Personalized Federated Learning
Lu, W., Yu, H., Wang, J., Teney, D., Wang, H., Zhu, Y., Chen, Y., Yang, Q., Xie, X. & Ji, X., 2025, Federated Learning in the Age of Foundation Models - FL 2024 International Workshops, Revised Selected Papers. Yu, H., Li, X., Xu, Z., Goebel, R. & King, I. (eds.). Springer, p. 19-35 17 p. (Lecture Notes in Computer Science; vol. 15501 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification
Tam, T. Y. C., Liang, L., Chen, K., Wang, H. & Wu, W., 2024, Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024. Cannataro, M., Zheng, H., Gao, L., Cheng, J., de Miranda, J. L., Zumpano, E., Hu, X., Cho, Y.-R. & Park, T. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 5104-5111 8 p. (Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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