机构

• 自动化研究所 [2]
• 长春光学精密机械与物... [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [3]
• 会议论文 [1]

发表日期

• 2022 [1]
• 2021 [2]
• 2010 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 IRDCLNet: Instance Segmentation of Ship Images Based on Interference Reduction and Dynamic Contour Learning in Foggy Scenes 期刊论文  OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 9, 页码: 6029-6043 作者:  Sun, Yuxin;  Su, Li;  Luo, Yongkang;  Meng, Hao;  Zhang, Zhi   |  收藏  |  浏览/下载：44/0  |  提交时间：2022/11/14 Marine vehicles  Image segmentation  Meteorology  Feature extraction  Interference  Object detection  Visualization  Foggy scene  ship instance segmentation  interference reduction module  dynamic contour learning   A Fog Covered Object Recognition Algorithm Based On Space And Frequency Network 期刊论文  OAI收割 INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2021, 卷号: 28, 期号: 2, 页码: 417-428 作者:  Cui, Ying;  Qiu, Shi;  Li, Tong   |  收藏  |  浏览/下载：42/0  |  提交时间：2021/05/25 Foggy image  fog concentration  estimation  target object recognition  fog removal  deep learning   FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 8, 页码: 1428-1439 作者:  Kunhua Liu;  Zihao Ye;  Hongyan Guo;  Dongpu Cao;  Long Chen   |  收藏  |  浏览/下载：26/0  |  提交时间：2021/06/11 Edge GAN  foggy images  foggy image semantic segmentation GAN  semantic segmentation   Real-time defogging processing of aerial images (EI CONFERENCE) 会议论文  OAI收割 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, September 23, 2010 - September 25, 2010, Chengdu, China 作者:  Liu G. 收藏  |  浏览/下载：37/0  |  提交时间：2013/03/25 A real-time image defogging processing method based on FPGA is proposed to increase low-contrast of the aerial images in foggy vision conditions. According to the high similarity of the contiguous frame histogram in video image  the histogram equalization algorithm is improved to enhance the image contrast. The median filter algorithm is used to eliminate the noise of the image. The experimental results demonstrate that the method can efficiently enhance the contrast  strengthen the detail and clarify definition for the fog-degraded aerial images. The visibility limit of the images has been increased to a time above. Simultaneously the method satisfies the real-time processing requirement of aerial video images  which has direct applications to the problem of poor visibility conditions. 2010 IEEE.