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Oracle PUP (product_user_profile) configuration and use

Recently in the Oracle Sqlplus Official document, the Sqlplus Security section describes the PUP mechanism. With this, I'll use the following:PUP (Product_user_profile) IntroductionProduct_user_profile is the next table in the system account to provide user-level security restrictions.The PUP setting is not valid for DBA authority users.Pups are only valid for local databases.1. SYSTEM User created Pup:SQLP

Oracle PUP (product_user_profile) configuration and use

Recently in the Oracle Sqlplus Official document, the Sqlplus Security section describes the PUP mechanism. Take this. I'm going to use the following:PUP (Product_user_profile) IntroductionProduct_user_profile is the next table in the system account to provide user-level security restrictions.The PUP setting is not valid for DBA authority users.Pups are only valid for local databases.1. SYSTEM User created

Significant regional detection of target detection---an image of a significant regional detection code and its effect diagram saliency region detection

++) {unsigned char*p= (unsigned char*) img->imagedata+h*img->widthstep;for (int w=0;wwidth;w++) {unsigned int t=0;t+=*p++;tt+=*p++;tt+=*p++;Imginput.push_back (t);}}Sal. Getsaliencymap (Imginput, Img->width, Img->height, imgsal);Vector to Iplimageint index=0;iplimage* imgout=cvcreateimage (Cvgetsize (IMG), ipl_depth_64f, 1);for (int h=0;hheight;h++) {Double*p= (double*) (imgout->imagedata+h*imgout->widthstep);for (int w=0;wwidth;w++) {*p++=imgsal[index++];}}Name.append (". saliency.jpg");Cvsavei

ILSVRC2016 Target Detection Task review-video target detection (VID)

Original URL: Http://www.cnblogs.com/laiqun/p/6501865.html The task of image target detection has made great progress in the past three years, and the detection performance has been significantly improved. But in video surveillance, vehicle-assisted driving and other fields, video-based target detection has a wider range of needs. Because of the problems such a

"Reprint" ILSVRC2016 Target Detection task review: Video target Detection (VID) _ Target Tracking

"Reprint" ILSVRC2016 Target Detection task review: Video target detection (VID) Reproduced from: http://geek.csdn.net/news/detail/133792The task of image target detection has made great progress in the past three years, and the detection performance has been greatly improved. But in the field of video surveillance, veh

Face detection--unitbox_ human face Detection (target detection)

This is an introduction to the face detection of technology from the view of the article: "2016 ACM MM unitbox:an Advanced Object Detection Network". The code should not be put out, but the implementation is relatively simple. (Interrupt a sentence, the paper said speed can reach 12fps, I'm a little panic, we look at science does not) —————————— split line —————————— Introduction Target

Pedestrian detection (pedestrian Detection) resource consolidation

first, the paper Articles in the review category: [1] D. Geronimo, and A. M.lopez. vision-based pedestrian Protection Systems for Intelligent vehicles, book, 2014. [2] P.dollar, C. Wojek,b Schiele, et al pedestrian detection:an evaluation of the state of the art [J]. IEEE transactions on Patternanalysis andmachine Intelligence, 2012, 34 (4): 743-761. [3] Cogs Zhi, Li Shaozi, Chen Shuyuan, etc. Survey of pedestrian detection technology [J]. Journal of

Deep learning target detection (object detection) series (eight) YOLO2

Deep learning target detection (object detection) series (i) r-cnnDeep learning target detection (object detection) series (ii) spp-netDeep learning target detection (object detection) series (iii) Fast R-CNNDeep learning target

JavaScript feature detection is not a browser detection _javascript technique

I have roughly translated some of the articles, may have misunderstood the place, please correct me. It is worth mentioning that the debate in the comments section is also worth seeing. Feature Detection At first, the front-end engineers objected to browser testing, which they thought was bad because it was not a future-oriented code and could not adapt to new browsers. A better approach is to use feature detec

__canny Edge detection algorithm for edge detection in OpenCV

OpenCV provides four different edge detection operators, or High-pass filters: Sobel,scharr and Laplacian operators and canny operators, the specific detection steps are as follows: image filtering : The algorithm of edge detection is based on first and second derivative of image gray value, but the derivative is usually sensitive to noise, so it is necessary to

Principle analysis of Lane line detection Hough line detection

http://blog.csdn.net/happy_stars_2016/article/details/52691255 First, lane line detection steps 1, Grayscale Grayscale key functions: Cvcvtcolorcvcvtcolor (iplimage* src, iplimage* DST, Cv_brg2gray);The last parameter is Cv_brg2gray, which indicates that the BRG picture (color picture) is converted to a grayscale picture (black and white). 2. Binary Value Image binary is to set the gray value of the pixel on the image to 0 or 255, that is, the enti

Target detection--pvanet:deep But lightweight neural Networks for real-time object detection

Reprinted from: http://blog.csdn.net/cv_family_z/article/details/52438372 https://www.arxiv.org/abs/1608.08021 In this paper, a variety of target detection for the problem, combined with the current technical achievements, to achieve a good result. We obtained solid results on well-known object detection benchmarks:81.8% MAP (mean average precision) on VOC2007 and 82. 5% MAP on VOC2012 (2nd place) while tak

Computer motherboard knowledge CPU automatic detection and hardware error detection

Computer now has become a daily necessities of life, then how much do you know about computers? The following small series for you to organize some common computer hardware knowledge, quickly to learn! Computer hardware, including all the physical parts of a computer, to differentiate between the data it contains or executes and the software that provides instructions for the hardware to complete the task. Computer hardware mainly includes: chassis, motherboard, bus, power, hard disk, storage c

Anomaly detection (Anomaly detection): Anomaly detection algorithm (Gaussian distribution applied)

Estimating the distribution of P (x)--Density estimationWe have a sample of M, each sample has n eigenvalues, each of which obeys different Gaussian distributions, and the formula in the assumption that each feature is independent, the effect of the formula is good, regardless of whether each feature is independent. The formula for the multiplication is expressed as shown.Estimating The distribution of P (x) is called the density estimation problem (density estimation)Anomaly

Hough Forest---Hofsonin (Hough forest) target detection algorithm for target detection

Hough Forest target detection is a more fashionable target detection algorithm, Juergen Gall is proposed on 2009 CVPR.Hough Forest sounds like a combination of Hough transformation +random forest, in fact, not exactly. It is more like the combination of decision forest and regression forest plus generalized Hough Transform: Each tree in the forest is not a classification tree or a regression tree, but each

Motion detection (foreground detection) (i) ViBe

motion detection (foreground detection) (i) ViBe Zouxy09@qq.com Http://blog.csdn.net/zouxy09 Because of monitoring the development of the demand, the current prospects of the research is still many, there have been many new methods and ideas. The personal understanding of the following is probably summed up as follows: Frame difference, background subtraction (GMM, CodeBook, sobs, Sacon, VIBE, W4, multi-fr

Big Data DDoS detection--ddos attack is essentially time series data, t+1 time data characteristics and T time strong correlation, so using hmm or CRF to do detection is inevitable! And a sentence of the word segmentation algorithm CRF no difference!

DDoS attacks are essentially time-series data, and the data characteristics of t+1 moments are strongly correlated with T-moments, so it is necessary to use HMM or CRF for detection! --and a sentence of the word segmentation algorithm CRF no difference!Note: Traditional DDoS detection is directly based on the IP data sent traffic to identify, through the hardware firewall. Big data scenarios are done for sl

Idle detection for Windows Phone/system idle Detection

The Windows Phone operating system can take actions to reduce power consumption on the device when it detects that the user or the current application is in an idle state. depending on the type of application you are creating, you may need to disable idle detection for users or applications. this topic explains how to modify the operating system's idle behavior. Important Note: This Windows Phone feature has certification requi

Example: Cocos2d-x physical engine: collision detection, cocos2d-x Collision Detection

Example: Cocos2d-x physical engine: collision detection, cocos2d-x Collision DetectionCollision detection is an important purpose of using the physical engine. Using the physical engine can perform precise collision detection, and the execution efficiency is also high.Use the event dispatch mechanism in Cocos2d-x 3.x to manage collision events, and EventListenerP

Javascript feature detection is not a browser detection _ javascript skills

In his blog Featuredetectionisnotbrowserdetection of the same name, NCZ describes a popular technology that has been used in front-end development-detection of users' browser platforms, and details historical development and advantages and disadvantages of various methods. I have roughly translated some articles and may have some misunderstandings. please correct me. It is worth noting that the comments are also worth reading. Feature

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