韩国全北国立大学Hyo Jong Lee教授学术报告

 

报告主题：Transfer deep feature learning for face sketch recognition

报告专家：Hyo Jong Lee  教授

报告时间：2019年11月1日(周五)  14:00-17:00

报告地点：信息管理学院H302报告厅

报告摘要：  

Even the deep learning, which has recently been deployed in face recognition, is not efficient for face sketch recognition due to the limited sketch datasets. We propose a novel face sketch recognition approach based on transfer learning. We design a three-channel convolutional neural network architecture in which the triplet loss is adopted in order to learn discriminative features and reduce intra-class variations. Moreover, we propose a hard triplet sample selection strategy to augment the number of training samples and avoid slow convergence. With the proposed method, facial features from digital photos and from sketches taken from the same person are closer; the opposite occurs if the digital photo and sketch are from different identities. Experimental results on multiple public datasets indicate that the proposed face sketch recognition method outperforms the existing approaches.

                                                        

专家介绍：

Hyo Jong Lee教授本科(1986)，硕士(1988)，与博士(1991)均毕业于美国犹他大学。自1991年起在全北国立大学拥有26年的教学科研经验。与此同时，李教授长期（7年）在美国加州大学兼职工作，他是Bristol University的访问教授，也是先进图像与信息技术中心主任，研究方向为图像处理、人工智能、并行计算以及生物信息学等。李教授承担过韩国国家研究基金(NRF)，韩国科技部(MSIP),韩国产学研项目等十多项科研课题。近五年来，发表43篇高水平期刊论文以及100多篇会议论文。拥有5项韩国专利以及1项国际专利。