sinkhole detection

Super Patrol Horse Detection system is the thousand Cloud's Data Security Laboratory (www.sucop.com) produced a free horse detection software. The software is designed to check for Web servers being hacked to grow script trojans and Web pages being embedded in malicious links. Click here to download Super Patrol Horse Detection system is a super Pat

Author: Lin shanmao Status detection firewall is currently the most widely used firewall to protect against hacker attacks. However, as the number of Web attacks targeted at the application layer increases, the effectiveness of the status detection firewall is getting lower and lower in attack protection. Status detection firewalls are not designed speci

Human body detection using rgb-d dataLucianospinello, Kai O. ArrasSummaryHuman detection is an important problem in robotics and intelligent systems. Previous research was done using cameras and 2D or 3D rangefinder. In this paper, we propose a new method of human body detection using rgb-d. We drew inspiration from hog (histogram of orientedgradients) and design

1. The existence and development inevitability of IDS (Intrusion Detection System) (1) complexity of network security itself, and passive defense methods are not powerful. (2) related firewalls: devices with network boundaries can be attacked by themselves, and some attacks are poorly protected. Not all threats come from outside the firewall. (3) Easy intrusion: Intrusion tutorials can be seen everywhere; various tools are at your fingertips; 2. Intru

1. The existence and development inevitability of IDS (Intrusion Detection System) (1) The complexity of network security and passive defense methods are insufficient. (2) related firewalls: devices with network boundaries can be attacked by themselves, and some attacks are poorly protected. Not all threats come from outside the firewall. (3) Easy intrusion: Intrusion tutorials are everywhere; various tools are at your fingertips 2. Intrusion

Collision detection and Sprite animations are the main components of all video games. Snail Bait (the game built in this article series) is no exception. Figure 1 shows the explosion of Snail Bait's running villain after a collision with a bee in the upper left corner. Figure 1. Practical application of collision detection In this article, learn how to: Detecting collisions Using the HTML5 Canvas cont

With the wide application of intrusion detection system, the requirement of testing and evaluating intrusion detection system is more and more urgent. Developers want to test and evaluate the deficiencies in the product, users want to test and evaluate to help themselves choose the right intrusion detection products. Based on the current research, this paper intr

This article explains in detail the network architecture and workflow of Faster R-CNN, which leads the reader to understand the principle of target detection, and the author also provides the Luminoth realization for everyone's reference. Luminoth implementation: GITHUB.COM/TRYOLABS/LUMINOTH/TREE/MASTER/LUMINOTH/MODELS/FASTERRCNN Last year, we decided to dig deeper into Faster r-cnn, read the original paper and other papers cited i

from:http://blog.csdn.net/u010402786/article/details/50596263 Prerequisites Moving target detection is an important subject in the field of computer image processing and image comprehension, and it is widely used in the fields of robot navigation, intelligent monitoring, medical image analysis, video image coding and transmission.—————————-——————— – classification of target detection methods First, a prio

With the increase in hacker technology, wireless LAN (WLANs) is under more and more threats. Session hijacking and DoS attacks caused by misconfiguration of wireless base stations (WAPs) affect the security of Wireless LAN. Wireless networks are not only attacked based on the traditional wired network TCP/IP architecture, but may also be threatened by the security issues of the 802.11 standard issued by the Institute of Electrical and Electronics Engineers (IEEE. To better detect and defend agai

DetectionAt present, the feature detection for Webshell is usually carried out through the static detection of characteristic ratio and file attribute anomaly, and the dynamic detection mode based on the access condition and behavior pattern feature, because spy type Webshell is often disguised as normal Web script file. Static feature

Now with the improvement of hacker technology, the wireless local area network (WLANS) is threatened more and more. The failure to configure a wireless base station (WAPS) causes session hijacking and denial of service attacks (Dos) to be like a plague that affects the security of wireless LANs in general. Wireless networks are vulnerable not only to the traditional wired network TCP/IP architecture but also to the security issues of the Institute of Electrical and Electronics Engineers (IEEE) r

Summarization of algorithms for moving target detection and tracking process Image preprocessingSome typical noises in digital images are: Gaussian noise comes from the noise of electronic circuit and low illumination or high temperature. The salt and pepper noise is similar to that of pepper and salt powder randomly distributed on the image, which is caused by the image cutting and the error caused by the transform domain; additive

Summarization of algorithm for moving target detection and tracking process Image preprocessing Several typical noises in digital images are: The Gaussian noise originates from the noise of the electronic circuit and the sensor noise caused by low illumination or high temperature, and the noise of salt and pepper is similar to the particles of pepper and powder which are randomly distributed on the image, mainly by the image cutting or the error cause

First, we look at the new progress of target detection from CVPR2016. The 2016 CVPR conference target detection method is mainly based on convolution neural network framework, Representative work has resnet (in faster r-cnn ResNet replacement Vgg), YOLO (regression detection framework), locnet (more accurate positioning), Hypernet (High level information of neura

Transferred from: http://lanbing510.info/2017/08/28/YOLO-SSD.html Prior to the emergence of deep learning, the traditional target detection method is probably divided into regional selection (sliding window), feature extraction (SIFT, hog, etc.), classifier (SVM, adaboost, etc.) three parts, the main problems have two aspects: on the one hand, sliding window selection strategy is not targeted, time complexity, window redundancy On the other hand, the

Objective In the DirectX SDK, the correlation function for collision detection is in xnacollision.h. Now, however, the previously implemented correlation functions have been transferred to the Windows SDK DirectXCollision.h and are in namespace DirectX. This consists mainly of four bounding boxes (bounding Volumes), and is implemented in the form of classes: Boundingsphere class-Surround ball (bounding Box) BoundingBox Class--axis aligned bou

Rapid objectdetection using a Boosted Cascade of simple Features fast target detection using the easy feature cascade classifierNote: Some translations are not allowed in a red fontTranslation, Tony,[email protected]Summary:This paper introduces a vision application of machine learning in target detection, which can process images quickly and achieve a higher recognition rate. The success of this work is du

Article Title: perfect solution for using the intrusion detection system in linux. Linux is a technology channel of the IT lab in China. Includes basic categories such as desktop applications, Linux system management, kernel research, embedded systems, and open source. 　　 Introduction to intrusion detection systems As more and more companies transfer their core services to the Internet, network security is

Girshick, Ross, et al. "Rich feature hierarchies for accurate object detection and semantic segmentation." Proceedings of the IEEE Conference on Computer vision and pattern recognition. 2014.The full name of R-CNN is REGION-CNN, which can be said to be the first algorithm to successfully apply deep learning to target detection. The fast r-cnn, Faster r-cnn are all based on R-CNN.Most of the traditional targ