武小荷 张宏志 任冬伟 左旺孟 王春宇 刘扬 刘国军
中心现有教师8人，其中博士生导师5人、教授1人、副教授6人、助理教授1人。研究方向主要包括机器学习、知识计算及其在计算机视觉和多模态任务理解中的应用。研究中心旨在立足学科前沿和国家重大需求，汇聚优势力量加强机器学习理论、模型和应用研究。中心累计完成国家科技部、国家自然科学基金、省部委基金和企业横向项目50余项，获得省部级科技进步奖5项。在CVPR/ICCV/NeurIPS/ECCV等顶级会议和T-PAMI/IJCV和IEEE Trans.等顶级期刊上发表论文150余篇，部分成果在国际上产生了较大影响，谷歌学术引用24,000余次。
标志性成果：模型引导的深度视觉计算
针对当前深度学习在底层视觉复原与增强和视觉语义理解中存在的共性和关键瓶颈问题，提出融合传统方法和已有知识/模型发展新型深度网络模型算法的创新研究思路，构建基于模型引导的深度视觉计算理论与方法体系，在图像去噪、视觉复原与增强、视觉语义理解方面取得了突破性进展，对相关领域的发展起到了重要的推动作用。提出的DnCNN取得显著优于传统方法的去噪性能与计算效率，已成为图像去噪领域的基准算法。构建了底层视觉先验建模、深度去噪网络和优化算法的有机结合机制，提出了图像复原网络和迭代自适应先验学习模型。2018年陕西省科学技术一等奖，2020年获黑龙江省自然科学一等奖。
Center on Machine Learning Research (CMLR) currently has 8 teachers, including 5 doctoral supervisors, 1 professor, 6 associate professors, and 1 assistant professor. The main research interests include machine learning, knowledge-based computing and their applications in computer vision and multi-modal understanding task. Towards the frontiers of ML disciplines and national requirements, CMLR aims at strengthening the studies on machine learning theories, models, and applications. The center has completed more than 50 research projects, including the funding of Ministry of Science and Technology, the National Natural Science Foundation of China (NSFC), provincial and ministerial funds and enterprise projects. CMLR also gained 5 provincial and ministerial scientific and technological progress awards. More than 150 papers have been published in top conferences such as CVPR/ICCV/NeurIPS/ECCV and top journals such as T-PAMI/IJCV and IEEE Transactions, and received more than 24,000 Google scholar citations.