百度技术副总监余凯博士访问实验室并受聘北邮兼职教授

报告题目:Image Recognition via Feature Learning

报告人:百度技术副总监、多媒体部负责人  余凯 博士

主持人:北邮模式识别实验室 高升

时间:  11月14日(周三)下午14:30 – 16:30

地点:   教3楼8层811会议室

Dr.  Kai YU

Abstract: The quality of visual features is crucial for a wide range of computer vision topics, e.g., scene classification, object recognition, and object detection, which are very popular in recent computer vision venues. All these image classification tasks have traditionally relied on hand-crafted features to try to capture the essence of different visual patterns. Fundamentally, a long-term goal in AI research is to build intelligent systems that can automatically learn meaningful feature representations from a massive amount of image data.

The primary objective of this talk is to introduce a paradigm of feature learning from unlabeled images, with an emphasis on applications to supervised image classification. We provide a comprehensive coverage of recently developed algorithms for learning powerful sparse nonlinear features, and showcase their superior performance on a number of challenging image classification benchmarks, including Caltech101, PASCAL, and the recent large-scale problem ImageNet. Furthermore, we describe deep learning and a variety of deep learning algorithms, which learn rich feature hierarchies from unlabeled data and can capture complex invariance in visual patterns.

个人简介:

余凯博士任百度技术副总监,多媒体部负责人,主要负责公司在语音、图像、音频等领域面向互联网和移动应用的技术研发。加盟百度前,余凯博士在美国NEC研究院担任Media Analytics部门主管(Department Head),领导团队在机器学习、图像识别、多媒体检索、视频监控,以及数据挖掘和人机交互等方面的产品技术研发。此前他曾在西门子公司任Senior Research Scientist。2011年曾在斯坦福大学计算机系客座主讲课程“CS121: 人工智能概论”。他在NIPS, ICML, CVPR, ICCV, ECCV,SIGIR, SIGKDD,TPAMI,TKDE等会议和杂志上发表了70多篇论文,引用超过2800次,H-index=28。曾担任机器学习国际会议ICML10, ICML11, NIPS11, NIPS12的Area Chair. 2012年他被评为中关村高端领军人才和北京市海聚计划高层次海外人才。余凯博士在南京大学获得学士和硕士学位,在德国慕尼黑大学获博士学位。

发表评论

电子邮件地址不会被公开。 必填项已用*标注