标题: DIABETIC RETINOPATHY DETECTION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORKS
作者: Chen, Yi-Wei
Wu, Tung-Yu
Wong, Wing-Hung
Lee, Chen-Yi
电子工程学系及电子研究所
Department of Electronics Engineering and Institute of Electronics
关键字: Diabetic Retinopathy Detection;Deep Convolutional Neural Networks;Image Classification
公开日期: 1-一月-2018
摘要: Diabetic retinopathy is the primary cause of blindness in the working-age population of the developed world. Diagnosing the disease heavily relies on imaging studies, which is a time consuming and a manual process performed by trained clinicians. Enhancing the accuracy and speed of the detection process can potentially have a significant impact on population health via early diagnosis and intervention. Motivated by this, we propose a recognition pipeline based on deep convolutional neural networks. In our pipeline, we design lightweight networks called SI2DRNet-v1 along with six methods to further boost the detection performance. Without any fine-tuning, our recognition pipeline outperforms state of the art on the Messidor dataset along with 5.26x fewer in total parameters and 2.48x fewer in total floating operations.
URI: http://hdl.handle.net/11536/150760
期刊: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
起始页: 1030
结束页: 1034
显示于类别:Conferences Paper