Department of Electronic Engineering, National Kaohsiung University of Science and Technology(Jiangong Campus)

公告消息, 最新消息(News), 演講訊息


演講訊息-Learning Deep Representations for Efficient and Effective Retrieval


中央研究院資訊科學研究所 研究員
國立台灣大學網路與多媒體研究所 合聘教授  
In this talk, I address two issues in content-based retrieval using deep learning: accuracy and efficiency. Deep convolutional neural networks (CNNs) have shown impressive performance on image classification. However, when the feature representations learned by deep CNNs are applied to image retrieval, the performance is still not as good as they are used for classification. We introduce an inter-batch reference learning approach based on the mean-average-precision criterion to handle this task. The learned feature space is better for relevant image search and can improve the retrieval accuracy. We also develop a method that learns binary hash codes from deep networks to speed up the search. Finally, I introduce some recent topics in my laboratory, including generative models and deep embedded vision.