中国科学院机构知识库网格系统: 检索

Multi-scale self-attention-based feature enhancement for detection of targets with small image sizes 期刊论文 OAI收割
PATTERN RECOGNITION LETTERS, 2023, 卷号: 166, 页码: 46-52
作者: Deng, Ying; Hu, Xingliang; Li, Bing; Zhang, Congxuan; Hu, Weiming

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收藏 | 浏览/下载：23/0 | 提交时间：2023/03/20

Detection of targets with small image sizes Feature enhancement Multi-scale combination Self-attention

D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 期刊论文 OAI收割
ACTA PHARMACEUTICA SINICA B, 2020, 卷号: 10, 期号: 7, 页码: 1239-1248
作者: Shi, Yulong; Zhang, Xinben; Mu, Kaijie; Peng, Cheng; Zhu, Zhengdan

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收藏 | 浏览/下载：45/0 | 提交时间：2020/12/24

COVID-19 SARS-CoV-2 Target prediction Multi-conformation Multi-site Docking D3Targets-2019-nCoV

Detecting different types of directional land cover changes using modis ndvi time series dataset 期刊论文 iSwitch采集
Remote sensing, 2016, 卷号: 8, 期号: 6, 页码: 23
作者: Xu, Lili; Li, Baolin; Yuan, Yecheng

收藏 | 浏览/下载：29/0 | 提交时间：2019/05/09

Time series Land cover change detection Ndvi Multi-targets Directional change Abrupt change Trend change

Improved multi-target radar TBD algorithm 期刊论文 OAI收割
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2015, 卷号: 26, 期号: 6, 页码: 1229-1235
作者: Bi Xin; Du Jinsong; Zhang Qingshi; Wang Wei

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收藏 | 浏览/下载：13/0 | 提交时间：2021/02/02

TRACK-BEFORE-DETECT HOUGH TRANSFORM PERFORMANCE TARGETS FILTER track before detect (TBD) Hough transform multi-dimensional Kalman filter

The application of variable-structure control in theodolite fast capture (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012, August 1, 2012 - August 2, 2012, Guangxi, China
Bing G.

收藏 | 浏览/下载：23/0 | 提交时间：2013/03/25

The high capability of O-E theodolite to track and acquire fast moving targets is required these years because of the rapid advancement of tested targets and automation of equipments. The traditional method of increasing the frequency width is limit. By using multi control models and velocity leading the capability to track and acquire fast moving target is improved highly. The theories and technologies discussed in this dissertation were tested with experiments. It verifies that the theoretical analysis in this dissertation is correct. (2012) Trans Tech Publications Switzerland.

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

收藏 | 浏览/下载：78/0 | 提交时间：2013/03/25

Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.

Multi-scale edge extraction based stereo matching algorithm (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010, December 11, 2010 - December 12, 2010, Chongqing, China
作者: Li L.

收藏 | 浏览/下载：14/0 | 提交时间：2013/03/25

In the field of robot vision edge feature based stereo matching algorithm can reconstruct the targets with clear contours which needs accurate and continuous target edges been extracted. In the paper the smoothing filter operator was designed based on the discrete criteria of edge extraction and its correspondence optimal linear filter. Edge extraction was carried out incorporated the nonmaximum suppression and two thresholds techniques. The discrete criteria based multi-scale edge extraction method was studied with full use of the multi-scale character of the edge information. The detected multi-scale edges were synthesized to obtain the accurate and continuous single pixel wide edge. Then an edge feature based stereo matching algorithm was proposed to obtain 3D information of target. The experimental results demonstrate that the method can effectively suppress disturbance in outdoor environment and reconstruct target contour clearly. (2011) Trans Tech Publications.

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：111/0 | 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).

Gimbal displacement error analysis on an electro-optical seeker (EI CONFERENCE) 会议论文 OAI收割
Optical Design and Testing IV, October 18, 2010 - October 20, 2010, Beijing, China
作者: Zhang X.; Zhang X.; Zhang X.

收藏 | 浏览/下载：35/0 | 提交时间：2013/03/25

It is essential to analyze the gimbal displacement errors for a seeker due to the importance for cueing of targets and tracking for the final approach. Otherwise for a seeker electro-driven with a concentric glass dome the large errors will decrease the picking pointing and tracking precision rooted from the displacement errors existing between the rotation center of the optical system and the gimbal. And the gimbaled camera system displacement errors are never eliminated but reduced due to the geometric errors consists of geometric tolerances of gimbal structure manufacture installation and vibration coming from working environment. In this paper the gimbal displacement errors in an electro-optically stabilized platform resulting from geometric errors and environment errors were analyzed and shown in detail. The mathematical modal of the gimbal displacement errors created based on multi-body dynamics demonstrated the connection between the gimbal displacement errors and the stabilized platform. Taking a visible light image seeker as a case the diameter is 120mm and the geometric tolerances came from the values of primary design and the vibration data came from the environmental vibration test on the pitch-yaw seeker and at the same time the errors resulting from installation were considered too. Based on calculating the maximum gimbal displacement error will reach to 0.2mm for pitching angle smaller than 40 and yawing angle smaller than 60. However the critical parts have been found out according to the probability theory and the reliability analysis successfully used in the paper and finally the maximum gimbal displacement error reduced to 0.1mm which is acceptable corresponding to the picking pointing and tracking precision for an optical imaging seeker. 2010 Copyright SPIE - The International Society for Optical Engineering.

Adaptive resolution storage system based on LOG-POLAR transform for multi-target trackers (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer Application and System Modeling, ICCASM 2010, October 22, 2010 - October 24, 2010, Shanxi, Taiyuan, China
作者: Zhang Y.

收藏 | 浏览/下载：22/0 | 提交时间：2013/03/25

The main constrained problem of the video monitoring and storage system is the contradiction between large field of view and storage space limitations. Not all of the video information introduced by the image sensors need to be recorded especially for some tracking system which has appointed functions to track specifically kinds of targets. For instance the system not only works for single target if the monitor is appointed for human face tracking but also can work for multi-targets. High reconstruction resolution in the fovea region enables the successive application of recognition modules without sacrificing their performance the best system appears to be concentrating on human face only and all the others considered being background the low reconstruction resolution in the periphery helps to reduce the video data. 2010 IEEE. the background regions needn't to be recorded in detail. For this purpose this letter presents a real-time foveate storage system which efficiently represents the video image in log-polar coordinates with the foveate point centered on the target