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	Improving Face Anti-spoofing via Advanced Multi-perspective Feature Learning 期刊论文 OAI收割 ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2023, 卷号: 19, 期号: 6, 页码: 18 作者: Wang, Zhuming; Xu, Yaowen; Wu, Lifang; Han, Hu; Ma, Yukun \| 收藏 \| 浏览/下载：31/0 \| 提交时间：2023/12/04 Face anti-spoofing multi-perspective universal cues
	Multi-perspective comparisons and mitigation implications of SO2 and NOx discharges from the industrial sector of China: a decomposition analysis 期刊论文 OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2018, 卷号: 25, 期号: 10, 页码: 9600-9614 作者: Jia, Junsong; Gong, Zhihai; Gu, Zhongyu; Chen, Chundi; Xie, Dongming \| 收藏 \| 浏览/下载：41/0 \| 提交时间：2018/06/04 Multi-perspective Decomposition analysis Industrial SO2 and NOx discharges LMDI China
	Multi-Perspectives' Comparisons and Mitigating Implications for the COD and NH3-N Discharges into the Wastewater from the Industrial Sector of China 期刊论文 OAI收割 WATER, 2017, 卷号: 9, 期号: 3, 页码: 18 作者: Jia, Junsong; Jian, Huiyong; Xie, Dongming; Gu, Zhongyu; Chen, Chundi \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2018/03/15 multi-perspective drivers COD and NH3-N discharges mitigating implication LMDI China
	Multi-Perspective Cost-Sensitive Context-Aware Multi-Instance Sparse Coding and Its Application to Sensitive Video Recognition 期刊论文 OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2016, 卷号: 18, 期号: 1, 页码: 76-89 作者: Hu, Weiming; Ding, Xinmiao; Li, Bing; Wang, Jianchao; Gao, Yan 收藏 \| 浏览/下载：51/0 \| 提交时间：2016/03/19 Cost-sensitive context-aware multi-instance sparse coding (MI-SC) horror video recognition multi-perspective multi-instance joint sparse coding (MI-J-SC) video emotional feature extraction violent video recognition
	Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：108/0 \| 提交时间：2013/03/25 Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).