ÎåÒ»²è¹Ý¶ù

>

Deep Learning

  • ÎåÒ»²è¹Ý¶ù

    HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis

    Deng, R.; Liu, Q.; Cui, C.; Yao, T.; Xiong, J.; Bao, S.; Li, H.; Yin, M.; Wang, Y.; Zhao, S.; Tang, Y.; Yang, H.; Huo, Y. “HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis.” Lecture Notes in Computer Science (including subseries Lecture Notes in… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound Images

    Li, H.; Oguz, B.; Arenas, G.; Yao, X.; Wang, J.; Pouch, A.; Byram, B.; Schwartz, N.; Oguz, I. “Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound Images.” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    MARVEL: Bringing Multi-Agent Reinforcement-Learning Based Variable Speed Limit Controllers Closer to Deployment

    Zhang, Y.; Quinones-Grueiro, M.; Zhang, Z.; Wang, Y.; Barbour, W.; Biswas, G.; Work, D. “MARVEL: Bringing Multi-Agent Reinforcement-Learning Based Variable Speed Limit Controllers Closer to Deployment.” IEEE Access, 2024 ÎåÒ»²è¹Ý¶ù, DOI: 10.1109/ACCESS.2024 ÎåÒ»²è¹Ý¶ù.3489474.  Variable Speed Limits (VSL) are used worldwide to help manage… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Semantic Segmentation and Classification of Active and Abandoned Agricultural Fields through Deep Learning in the Southern Peruvian Andes

    Zimmer-Dauphinee, J.; Wernke, S.A. “Semantic Segmentation and Classification of Active and Abandoned Agricultural Fields through Deep Learning in the Southern Peruvian Andes.” Remote Sensing, Volume 16, Issue 19, 2024 ÎåÒ»²è¹Ý¶ù, Article 3546, DOI: 10.3390/rs16193546.  In pre-Hispanic times, the Andean people built massive… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Wasserstein task embedding for measuring task similarities

    Liu, X.; Bai, Y.; Lu, Y.; Soltoggio, A.; Kolouri, S. “Wasserstein task embedding for measuring task similarities.” Neural Networks, Volume 181, 2025, Article 106796, DOI: 10.1016/j.neunet.2024 ÎåÒ»²è¹Ý¶ù.106796.    Measuring the similarity between different tasks is important for various machine learning problems,… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Zero-shot prompt-based video encoder for surgical gesture recognition

    Rao, M.; Qin, Y.; Kolouri, S.; Wu, J.Y.; Moyer, D. “Zero-shot prompt-based video encoder for surgical gesture recognition.” International Journal of Computer Assisted Radiology and Surgery, 2024 ÎåÒ»²è¹Ý¶ù, DOI: 10.1007/s11548-024-03257-1.  This study explores how to build a system that can recognize surgical gestures… Read More

    Nov. 21, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Field-of-view extension for brain diffusion MRI via deep generative models

    Gao, Chenyu, Bao, Shunxing, Kim, Michael E., Newlin, Nancy R., Kanakaraj, Praitayini, Yao, Tianyuan, Rudravaram, Gaurav, Huo, Yuankai, Moyer, Daniel, Schilling, Kurt, Kukull, Walter A., & Toga, Arthur W. (2024 ÎåÒ»²è¹Ý¶ù). Field-of-view extension for brain diffusion MRI via deep generative models. Journal of Medical Imaging, 11(4), 044008. https://doi.org/10.1117/1.JMI.11.4.044008… Read More

    Sep. 22, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Time-Series Few Shot Anomaly Detection for HVAC Systems

    Huang, Yuxin, Coursey, Austin, Quinones-Grueiro, Marcos, & Biswas, Gautam. (2024 ÎåÒ»²è¹Ý¶ù). Time-series few shot anomaly detection for HVAC systems. In Proceedings of the 12th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS 2024 ÎåÒ»²è¹Ý¶ù), Ferrara, Italy, June 4-7, 2024 ÎåÒ»²è¹Ý¶ù, Volume 58, Issue 4, Pages 426-431. Read More

    Sep. 22, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Genetic Improvement for DNN Security

    Baxter, Hunter, Huang, Yu, & Leach, Kevin. (2024 ÎåÒ»²è¹Ý¶ù). Genetic improvement for DNN security. In Proceedings of the 13th International Genetic Improvement Workshop (GI@ICSE 2024 ÎåÒ»²è¹Ý¶ù), Lisbon, Portugal, April 16, 2024 ÎåÒ»²è¹Ý¶ù, Pages 11-12. https://doi.org/10.1145/3643692.3648261 This study explores a novel application of Genetic Improvement (GI) in enhancing the security of Deep Neural Networks… Read More

    Sep. 22, 2024 ÎåÒ»²è¹Ý¶ù

  • ÎåÒ»²è¹Ý¶ù

    Mitigating Over-Saturated Fluorescence Images Through a Semi-Supervised Generative Adversarial Network

    Bao, Shunxing, Guo, Junlin, Lee, Ho Hin, Deng, Ruining, Cui, Can, Remedios, Lucas W., Liu, Quan, Yang, Qi, Xu, Kaiwen, Yu, Xin, Li, Jia, & Li, Yike. (2024 ÎåÒ»²è¹Ý¶ù). Mitigating over-saturated fluorescence images through a semi-supervised generative adversarial network. In Proceedings of the 21st IEEE International Symposium on Biomedical Imaging (ISBI… Read More

    Sep. 22, 2024 ÎåÒ»²è¹Ý¶ù