Relevant bibliographies by topics / Forward detection systems

Academic literature on the topic 'Forward detection systems'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Forward detection systems"

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Kabakchiev, Hristo, Vera Behar, Ivan Garvanov, Dorina Kabakchieva, Avgust Kabakchiev, and Hermann Rohling. "FSR Systems for Detection of Air Objects Using Cosmic Radio Emissions." Sensors 21, no. 2 (January 11, 2021): 465. http://dx.doi.org/10.3390/s21020465.

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The paper analyses the possibility of Forward Scatter Radar (FSR) systems to detect airplanes using cosmic emission from pulsars and planets (pulsar, Sun, Moon). A suboptimal multichannel algorithm for joint detection and evaluation of the parameters of the forward scattering signal created by an airplane (duration and velocity) is proposed, with preliminary compensation of the powerful direct signal emitted by cosmic sources (pulsar, Sun and Moon). The expressions for calculation of the Signal-to-Noise Ratio (SNR) at the input of the detector and the compensator are obtained. The detection characteristics are also obtained, and the requirements for the suppression coefficient of the compensator are evaluated. A methodology for calculating the maximum distance for detecting an aircraft using a described algorithm is proposed. The obtained results show that due to the Forward Scatter (FS) effect, there is the theoretical possibility to detect airplanes at close ranges by FSRs, which use very weak signals from cosmic sources.
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Kabakchiev, Hristo, Vera Behar, Ivan Garvanov, Dorina Kabakchieva, Avgust Kabakchiev, and Hermann Rohling. "FSR Systems for Detection of Air Objects Using Cosmic Radio Emissions." Sensors 21, no. 2 (January 11, 2021): 465. http://dx.doi.org/10.3390/s21020465.

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The paper analyses the possibility of Forward Scatter Radar (FSR) systems to detect airplanes using cosmic emission from pulsars and planets (pulsar, Sun, Moon). A suboptimal multichannel algorithm for joint detection and evaluation of the parameters of the forward scattering signal created by an airplane (duration and velocity) is proposed, with preliminary compensation of the powerful direct signal emitted by cosmic sources (pulsar, Sun and Moon). The expressions for calculation of the Signal-to-Noise Ratio (SNR) at the input of the detector and the compensator are obtained. The detection characteristics are also obtained, and the requirements for the suppression coefficient of the compensator are evaluated. A methodology for calculating the maximum distance for detecting an aircraft using a described algorithm is proposed. The obtained results show that due to the Forward Scatter (FS) effect, there is the theoretical possibility to detect airplanes at close ranges by FSRs, which use very weak signals from cosmic sources.
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Ray, Loye Lynn, and Henry Felch. "Improving Performance and Convergence Rates in Multi-Layer Feed Forward Neural Network Intrusion Detection Systems." International Journal of Strategic Information Technology and Applications 5, no. 3 (July 2014): 24–36. http://dx.doi.org/10.4018/ijsita.2014070102.

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Today's anomaly-based network intrusion detection systems (IDSs) are plagued with detecting new and unknown attacks. The review of the literature builds ideas for researching the problem of detecting these attacks using multi-layered feed forward neural network (MLFFNN) IDSs. The scope of the paper focused on a review of the literature from primarily 2008 to the present found in peer-review and scholarly journals. A key word search was used to compare and contrast the literature to find strengths, weaknesses and gaps. The significance of the research found that further work is needed to improve the performance and convergence rates of MLFFNN IDSs. This literature review contributes to the area of intrusion detection by looking at the effects of architecture, algorithms, and input data on the performance and convergence rates of MLFFNN IDSs.
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de Almeida, A. L. F., C. A. R. Fernandes, and Daniel Benevides da Costa. "Multiuser Detection for Uplink DS-CDMA Amplify-and-Forward Relaying Systems." IEEE Signal Processing Letters 20, no. 7 (July 2013): 697–700. http://dx.doi.org/10.1109/lsp.2013.2260738.

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Mao, Minghe, Ning Cao, Yunfei Chen, and Haobing Chu. "Novel noncoherent detection for multi-hop amplify-and-forward relaying systems." International Journal of Communication Systems 29, no. 7 (December 18, 2015): 1293–304. http://dx.doi.org/10.1002/dac.3099.

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Hindriks, Rikkert. "Lag-invariant detection of interactions in spatially-extended systems using linear inverse modeling." PLOS ONE 15, no. 12 (December 11, 2020): e0242715. http://dx.doi.org/10.1371/journal.pone.0242715.

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Measurements on physical systems result from the systems’ activity being converted into sensor measurements by a forward model. In a number of cases, inversion of the forward model is extremely sensitive to perturbations such as sensor noise or numerical errors in the forward model. Regularization is then required, which introduces bias in the reconstruction of the systems’ activity. One domain in which this is particularly problematic is the reconstruction of interactions in spatially-extended complex systems such as the human brain. Brain interactions can be reconstructed from non-invasive measurements such as electroencephalography (EEG) or magnetoencephalography (MEG), whose forward models are linear and instantaneous, but have large null-spaces and high condition numbers. This leads to incomplete unmixing of the forward models and hence to spurious interactions. This motivated the development of interaction measures that are exclusively sensitive to lagged, i.e. delayed interactions. The drawback of such measures is that they only detect interactions that have sufficiently large lags and this introduces bias in reconstructed brain networks. We introduce three estimators for linear interactions in spatially-extended systems that are uniformly sensitive to all lags. We derive some basic properties of and relationships between the estimators and evaluate their performance using numerical simulations from a simple benchmark model.
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Schreiner, K. "Landmine detection research pushes forward, despite challenges." IEEE Intelligent Systems 17, no. 2 (2002): 4–7. http://dx.doi.org/10.1109/5254.995459.

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Lu, You Li, and Jun Luo. "Imbalanced Data Detection Kernel Method in Closed Systems." Advanced Materials Research 756-759 (September 2013): 3652–58. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3652.

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Under the study of Kernel Methods, this paper put forward two improved algorithm which called R-SVM & I-SVDD in order to cope with the imbalanced data sets in closed systems. R-SVM used K-means algorithm clustering space samples while I-SVDD improved the performance of original SVDD by imbalanced sample training. Experiment of two sets of system call data set shows that these two algorithms are more effectively and R-SVM has a lower complexity.
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Veselov, V. V., A. M. Nechipai, E. A. Poltoryhina, and A. V. Vasilchenko. "FIRST EXPERIENCE IN FULL-SPECTRUM COLONOSCOPY." Koloproktologia, no. 2 (June 30, 2017): 36–46. http://dx.doi.org/10.33878/2073-7556-2017-0-2-36-46.

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Colonoscopy with a forward-viewing camera leaves regions that are not visualized in detail. Thus development of video-enoscopy systems with wide angle of view is needed. Full-spectrum colonoscopes providing image of Ultra HD 4K quality are now available in Russia. MATERIALS AND METHODS. Seventy patents were assessed with a full-spectrum colonoscope. In 51 (72,8°%) of them the procedure was performed also for physician's training purposes. Fifteen (21,4%) patients underwent simultaneous full-spectrum and forward-viewing colonoscopies, while in 4 (5,7%) full-spectrum endoscope was used to visualize lesions that were non-assessable with traditional equipment. RESULTS. Applying Jull-spectrum colonoscopy for diagnosis resulted in detecting 170 polyps in 51 patients (polyp detection rate was 47,1%). Simultaneous use of full-spectrum colonoscope after forward-viewing equipment led to 9 additional polyps detection in one patient and 23 additional polyps in another one. In 7 patents full-spectrum colonoscopy allowed detection of polyps that were not found via forward-viewing equipment. CONCLUSION. During full-spectrum colonoscopy inner colonic surface can be visualized with an angle of view of 330° which is twice more than video-capturing area ofa standard forward-viewing endoscope. The equipment allows to significantly increase adenoma detection rate.
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He Yucheng, Qiao Ying, and Zhou Lin. "Generalized maximum likelihood noncoherent block detection for decode-and-forward relay systems." China Communications 11, no. 4 (April 2014): 163–71. http://dx.doi.org/10.1109/cc.2014.6827578.

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Dissertations / Theses on the topic "Forward detection systems"

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Mukhopadhyay, Shayok. "Robust forward invariant sets for nonlinear systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52311.

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The process of quantifying the robustness of a given nonlinear system is not necessarily trivial. If the dynamics of the system in question are not sufficiently involved, then a tight estimate of a bound on system performance may be obtained. As the dynamics of the system concerned become more and more involved, it is often found that using the results existing in the literature provides a very conservative bound on system performance. Therefore, the motivation for this work is to develop a general method to obtain a less conservative estimate of a bound on system performance, compared to the results already available in literature. The scope of this work is limited to two dimensions at present. Note that working in a two dimensional space does not necessarily make the objective easily achievable. This is because quantifying the robustness of a general nonlinear system perturbed by disturbances can very easily become intractable, even on a space with dimension as low as two. The primary contribution of this work is a computational algorithm, the points generated by which are conjectured to lie on the boundary of the smallest robust forward invariant set for a given nonlinear system. A well known path-planning algorithm, available in existing literature, is leveraged to make the algorithm developed computationally efficient. If the system dynamics are not accurately known, then the above computed approximation of an invariant set may cease to be invariant over the given finite time interval for which the computed set is expected to be invariant. Therefore, the secondary contribution of this work is an algorithm monitoring a computed approximation of an invariant set. It is shown that for a certain type of systems, this secondary monitoring algorithm can be used to detect that a computed approximation of an invariant set is about to cease to be invariant, even if the primary algorithm computed the set based on an unsophisticated dynamical model of a system under consideration. The work related to computing approximations of invariant sets is tested mainly with the curve tracking problem in two dimensions. The algorithm monitoring whether a computed approximation of an invariant set is about to cease to be invariant is inspired by work related to detecting Lithium-ion (Li-ion) battery terminal voltage collapse detection.
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Ma, Jun. "Channel estimation and signal detection for wireless relay." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37082.

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Wireless relay can be utilized to extend signal coverage, achieve spatial diversity by user cooperation, or shield mobile terminals from adverse channel conditions over the direct link. In a two-hop multi-input-multi-output (MIMO) amplify-and-forward (AF) relay system, the overall noise at the destination station (DS) consists of the colored noise forwarded from the relay station (RS) and the local white noise. We propose blind noise correlation estimation at the DS by utilizing statistics of the broadband relay channel over the RS-DS hop, which effectively improves signal detection at the DS. For further performance improvement, we also propose to estimate the two cascaded MIMO relay channels over the source-RS and the RS-DS links at the DS based on the overall channel between the source and the DS and the amplifying matrix applied at the RS. To cancel cross-talk interference at a channel-reuse-relay-station (CRRS), we utilize the random forwarded signals of the CRRS as equivalent pilots for local coupling channel estimation and achieve a much higher post signal-to-interference ratio (SIR) than the conventional dedicated pilots assisted cancellers without causing any in-band interference at the DS. When an OFDM-based RS is deployed on a high-speed train to shield mobile terminals from the high Doppler frequency over the direct link, inter-subchannel interference (ICI) mitigation is required at the RS. By utilizing statistics of the channel between the base station and the train, we develop both full-rate and reduced-rate OFDM transmission with inherent ICI self-cancellation via transmit and/or receive preprocessing, which achieve significant performance improvement over the existing ICI self-cancellation schemes.
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Wen, Wen. "Forward Leading Vehicle Detection for Driver Assistant System." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42127.

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Keeping a safe distance from the forward-leading vehicle is an essential feature of modern Advanced Driver Assistant Systems (ADAS), especially for transportation companies with a fleet of trucks. We propose in this thesis a Forward Collision Warning (FCW) system, which collects visual information using smartphones attached for instance to the windshield of a vehicle. The basic idea is to detect the forward-leading vehicle and estimate its distance from the vehicle. Given the limited resources of computation and memory of mobile devices, the main challenge of this work is running CNN-based object detectors at real-time without hurting the performance. In this thesis, we analyze the bounding boxes distribution of the vehicles, then propose an efficient and customized deep neural network for forward-leading vehicle detection. We apply a detection-tracking scheme to increase the frame rate of vehicle detection and maintain good performance. Then we propose a simple leading vehicle distance estimation approach for monocular cameras. With the techniques above, we build an FCW system that has low computation and memory requirements that are suitable for mobile devices. Our FCW system has 49% less allocated memory, 7.5% higher frame rate, and 21% less battery consumption speed than popular deep object detectors. A sample video is available at https://youtu.be/-ptvfabBZWA.
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Paulo, Eugene P. "Comparison of Janus and field test aircraft detection ranges for the line-of-sight forward heavy system." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/26417.

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Wåhlin, Peter. "Enhanching the Human-Team Awareness of a Robot." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16371.

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The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot.
Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot.

The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.

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Huang, Shun-Wei, and 黃舜暐. "Weather-adapted Vehicle Detection and Verification For Forward Collision Warning Systems." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/ga43cj.

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碩士
國立中央大學
資訊工程學系
104
There were lots of deaths caused by traffic accidents of rear-end collision, advanced driver assistance systems (ADASs) has become an important research topic in recent years. To prevent these fatalities, forward collision warning (FCW) systems have been proposed to protect drivers from the danger due to paying no attention to forward traffic situations. Not only FCW systems but also many other ADASs such as lane departure warning (LDW), blind spot detection (BSD), pedestrian collision warning (PCW), etc. have been developed to assist drivers. In this thesis, we present a weather-adaptive forward collision warning system, which would help drivers to avoid collisions to the preceding vehicles or obstacles. In the proposed FCW system, the local features such as horizontal and vertical edges are first calculated. Then edge maps are bi-leveled using a learning thresholding method to adapt the intensity variation of captured images, so that the extraction of edge points is less influenced by bad weather conditions. Third, the preserved edge points are used to generate possible objects . Fourth, the objects are selected based on edge response, location, and symmetry of object candidates to generate vehicle candidates. Three candidate generation schemes are hierarchically designed to extract vehicle candidates in various weather conditions. At last, a method based on principal component analysis (PCA) is proposed to verify the vehicle candidates. PCA is a technique used to extract the important features of a set of vehicle images. Each extracted feature describes a characteristic of vehicle appearance which is defined as a global feature. Depending on the extracted features, a candidate region can be decomposed and reconstructed. The similarity between the original regions and the reconstructed regions are measured to verify the vehicle candidates. Theoretically, PCA method is used to remove the non-vehicle candidates to reduce the false alarm. The proposed FCW system has been test and evaluated on various weather conditions. The average accuracies of the proposed FCW system in clear and bad weather conditions are 98.5% and 71.8%, respectively. In our experiment, the system execution speed of approximately 50 frames per second and camera captured 30 frames per second, so the system can achieve real-time vehicle detection.
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Liu, Wen-Tong, and 劉文通. "Vision‐based Lane Tracking and Forward Vehicle Detection Advanced Driver Assistance Systems." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/32000490219636445352.

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碩士
國立臺灣科技大學
電機工程系
102
Advanced driver assist systems (ADAS) are technologies that provide the driver with essential information when driving and lead to an increase in safe driving. On a long stretch of highway, the lane departure and forward vehicle collision are very important issues for drivers. The proposed ADAS focuses on implementing lane tracking, lane departure detection and forward vehicle detection by using the image processing techniques. In this thesis, our algorithms can provide the following basic information: (1) Lane detection, (2) Lane tracking, (3) Forward vehicle detection. In lane detection, our algorithms first combine the edge distribution function (EDF) with lane marking filter to improve the effects of non-lane marking noise and then detect the lane marking correctly. In lane tracking, the proposed method can predict the region of interest (ROI) of lane marking by the properties of continuous video in the next frame. Then, ROI is examined to track lane marking by Hough transform. In addition, no matter whether a vehicle is changing lane or passing exit-ramp, our algorithms can keep track of the lane marking smoothing. In forward vehicle detection, the position of the forward vehicle inside its own lane is determined by the features of rear shapes of vehicle, such as shadow, horizontal edge, vertical edge, symmetry and image density. Through video streams with resolution of 640×360 pixels, the experimental results achieve the average detection rate of lane tracking at 97.00% with the average processing time 5.4 ms per frame and the average detection rate of forward vehicle at 84.86% with average processing time 2 ms per frame.
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Hamdane, Hédi. "Improvement of pedestrian safety: response of detection systems to real accident scenarios." Thesis, 2016. http://hdl.handle.net/2440/119694.

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The scope of this research concerns pedestrian active safety. Several primary safety systems have been developed for vehicles in order to detect a pedestrian and to avoid an impact. These systems analyse the forward path of the vehicle through the processing of images from sensors. If a pedestrian is identified on the vehicle trajectory, these systems employ emergency braking and some systems may potentially employ emergency steering. Methods for assessing the effectiveness of these systems have been developed. But, it appears difficult to determine the relevance of these systems in terms of pedestrian protection. The general objective of this research was to test the response of these systems in many accident configurations. The first step consisted of gathering a sample of a hundred of accidents involving vehicles with pedestrians. These accidents were provided from accident databases of two laboratories LMA and CASR. Data of these accidents were recorded in sufficient detail from in-depth investigation which enables reconstructing the trajectory of the vehicle and pedestrian prior to the collision. The second step was to analyse qualitatively and quantitatively the data of the selected accidents. These accidents were reconstructed to simulate the pre-crash conditions. From this accident reconstruction, factors relevant to the primary safety of pedestrians were deduced. The next step consisted of coupling the vehicle dynamic behaviour with a primary safety system in order to confront these systems to real accident configurations. The potential of these systems is studied by verifying the feasibility of deploying an autonomous emergency manoeuvre during the timeline of the accident and according to the vehicle dynamic capabilities: i.e. verifying the possibilities in terms of crash avoidance. Based on this procedure, three modelling methods were developed: a first method testing a system to each accident configuration and two others using graphs of evaluation from a parametric study realised on a generic system. The results of the three methods were then discussed. Finally, as a perspective, the last study will approach crash mitigation. As a consequence of an active safety system response, the vehicle impact speed is reduced. The effect of speed reduction on variations in impact conditions will be then addressed to measure the potential safety impact of these systems on pedestrian protection.
Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2016.
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Chuang, Shih-Hsien, and 莊士賢. "Nighttime Forward Vehicle Deceleration Detection System for Motorcycle." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/23198101113657008169.

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碩士
國立臺灣師範大學
資訊工程學系
104
Vision-based driver assistance systems and its related technologies were started to pay attention and develop from about 20 years ago. Visual analyzing the road situation in front of vehicles through camera to assist drivers. Vision-based driver assistance systems for automobile has been gradually consummated. In contrast, vision-based driver assistance systems for motorcycle went unheeded. The quantity of motorcycle and automobile increases year by year, and the quantity of motorcycle is fifty thousand more than automobile per year. Summarizes the above situation causes that automobile traffic accident rate reduces year after year, but motorcycle traffic accident rate rises every year. Daytime forward vehicle detection technology has been matured by degrees, but there is not so much researchers developing and researching at nighttime. By literatures in recent years of nighttime forward vehicle detection technology, many researches confirm the location of vehicle through related technologies about taillight detection. Therefore this study will use taillight detection to confirm the location of vehicle. Because it has to do a forward vehicle deceleration detection, forward vehicle decelerates or not will be determined by the brake-lights activates or not. When the motorcycle turns a corner, this study will adjust Region of Interest (ROI). There will not be traffic accidents with the forward vehicle when the vehicle stop moving as the red traffic light shows. So it hasn’t to do a taillight detection and brake-light detection. Therefore our system needs to detect forward vehicle move or not. The shape of taillight in the recent years is not only traditional circle but also irregular shape or elongated shape, and therefore this study will aim at the characteristic of surrounding light source around the taillight to do a taillight detection. This study will use illumination and threshold to determine brake-light on or off, and this dynamic threshold according to the distance between taillight and camera. The illumination of some activated brake-lights is lower than our determined threshold, and some non-brake of taillights are higher than it. It will lead to failure of brake-light detection. So our system will adjust threshold specifically to increase the accuracy rate of brake-light detection. Our system experiments on sunny day, rainy day, in the tunnel, and on many kinds of roads. The experiment result shows that it will get the higher accuracy rate without considering the consequence of taillight detection with the reflection of red lights. And our system expects that the reflection of red lights can be filter in the future to increase the accuracy rate of taillight detection. In this study, if it doesn’t consider raindrop dripping on the camera lens on rainy day, the accuracy rate of brake-light detection is about 90%
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Chiu, Shan-Ting, and 邱慎廷. "The Study of a Forward Vehicle Detection Warning System with Multiple-lane Detection." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/51565014465278631081.

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碩士
國立交通大學
電機與控制工程系所
98
In This thesis the technique of image processing and computer vision theorem are applied to lane detection and vehicle detection. In the meantime, the algorithm is also applied on TI-DM642 for driving assistance system (DAS). The system has been working in different environment such as expressway, urban area and tunnel. Furthermore the algorithm is such robust to be verified with all weather condition like sunny day, cloudy day, evening, morning, night and rainy day. In the lane detection, CCD camera is used to grab the front view, and then the algorithm detects the lane making to contribute a real lane model. This model is applied to estimate and narrow the searching area in order to increase the accuracy and reduce the computation. The lane detection system has been verified successfully in expressway and urban road. Moreover, the system has been equipped on Taiwan iTS-1 (the first intelligence car of Taiwan) as vision system and combines with control system to accomplish lane keeping and lane change. The vehicle detection uses the lane model to build basic vehicle parameters and sets the ROI from the result of lane detection. Algorithm will select multiple possible objects those have strong vehicle characteristics. After feature extraction, the vehicles will be verified with the classify rules. The thesis considers kinds of the vehicle features in different weathers condition and overcomes lots of influence from environment like the text on the road, the strong shadows and light, and the reflected light from the road surface. Even with rainfall and windscreen wiper, the system works successfully. The detection has no relationship with the day or night, so it has good performance at smooth light changing or sudden light changing. With the lane model from lane detection, the algorithm could establish the multiple lane boundaries and finish the multiple forward car detection. At same time, the distance of the forward vehicle can be calculated, and the systems will warn driver that he is in the dangerous distance.
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Books on the topic "Forward detection systems"

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D, Anderson Charles. Flight crew interface aspects of forward-looking airborne windshear detection systems: Final report. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1993.

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Paulo, Eugene P. Comparison of Janus and field test aircraft detection ranges for the line-of-sight forward heavy system. Monterey, Calif: Naval Postgraduate School, 1991.

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Allsop, Cheryl. Organizing the Organizational Memory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198747451.003.0007.

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This chapter concerns ‘organizing the organizational memory’, that is, the fundamental processes, practices, and procedures required to enable cold case reviews to take place. The advances in DNA profiling techniques and technologies have created a growth of opportunities for reviewing cold cases, and in this chapter it will become clear how this investigative potential has created new problems requiring the development of a system of working before a review can take place, suggesting the need to look forward and back in the review process. What emerges is a process of ‘back engineering’ and forward planning, a collection of routine activities centred on finding opportunities to identify and connect suspects to the unsolved crimes revealing the realities of such work, which is often mundane, far from the gloss and glamour depicted by media representations. The challenges to achieving a successful detection are also laid out.
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Walczak, Jean-Sébastien. Understanding the responsiveness of C-fibres. Edited by Paul Farquhar-Smith, Pierre Beaulieu, and Sian Jagger. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198834359.003.0006.

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In the paper discussed in this chapter, Ainsley Iggo used electrophysiology to characterize mechanosensory fibres from the saphenous nerve in cats. Using fine techniques of dissection he recorded from single units and therefore could discriminate between the various types of sensitivity of afferent fibres. This article describes properties of primary afferent neurons in response to precise calibrated mechanical stimuli and focused on mechanical sensitivity of C-fibres. In addition, the manuscript describes the properties of skin-receptor fields. The paper showed that not all C-fibres responded to high-intensity stimuli and that receptive fields were quite small. In addition, it provided a qualitative evaluation of stimuli necessary to activate those fibres. Hence, by isolating fibres that responded only to strong stimulation, this article showed that the peripheral nervous system is equipped with a specific apparatus for detecting nociceptive stimuli; this was a great step forward in understanding the physiology of pain.
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Book chapters on the topic "Forward detection systems"

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Wang, Zhangyu, Tony Lee, Michael Leung, Simon Tang, Qiang Zhang, Zining Yang, and Virginia Cheung. "A Forward Train Detection Method Based on Convolutional Neural Network." In Advances in Intelligent Systems and Computing, 129–35. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39512-4_21.

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Ahmed, Abdulghani Ali. "Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network." In Advances in Intelligent Systems and Computing, 24–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03302-6_3.

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Pratapur, Satish, and D. C. Shubangi. "Detection of Forgery in the JPEG Images Using Forward Quantization Noise Method." In Algorithms for Intelligent Systems, 31–43. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-6707-0_3.

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Yadav, Gaurav Kumar, Tarun Kancharla, and Smita Nair. "Real Time Vehicle Detection for Rear and Forward Collision Warning Systems." In Advances in Computing and Communications, 368–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22726-4_39.

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Ortega, Juan Diego, Marcos Nieto, Andoni Cortes, and Julian Florez. "Perspective Multiscale Detection of Vehicles for Real-Time Forward Collision Avoidance Systems." In Advanced Concepts for Intelligent Vision Systems, 645–56. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02895-8_58.

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Shrivastava, Amit. "Detection of Induction Motor Bearing Fault Using Time Domain Analysis and Feed-Forward Neural Network." In Algorithms for Intelligent Systems, 359–69. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1059-5_40.

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Martin, Don Joe, Aaditya Saraiya, V. Kalaichelvi, and R. Karthikeyan. "Vision-Based Forward Kinematics Using ANN for Weld Line Detection with a 5-DOF Robot Manipulator." In Advances in Intelligent Systems and Computing, 309–18. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8237-5_30.

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Ahmed, Sajjad, Klestia Balla, Knut Hinkelmann, and Flavio Corradini. "Fact Checking: Detection of Check Worthy Statements Through Support Vector Machine and Feed Forward Neural Network." In Advances in Intelligent Systems and Computing, 520–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73103-8_37.

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Kirubavathi Venkatesh, G., and R. Anitha Nadarajan. "HTTP Botnet Detection Using Adaptive Learning Rate Multilayer Feed-Forward Neural Network." In Information Security Theory and Practice. Security, Privacy and Trust in Computing Systems and Ambient Intelligent Ecosystems, 38–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30955-7_5.

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Lee, Pei Shyuan, Majdi Owda, and Keeley Crockett. "The Detection of Fraud Activities on the Stock Market Through Forward Analysis Methodology of Financial Discussion Boards." In Advances in Intelligent Systems and Computing, 212–20. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03405-4_14.

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Conference papers on the topic "Forward detection systems"

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Baptista, Renan Martins, and Carlos Henrique Wildhagen Moura. "Leak Detection Systems for Multiphase Flow: Moving Forward." In 2002 4th International Pipeline Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/ipc2002-27283.

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Multiphase flow is one of the most difficult situations for leak detection in pipelines, due to several reasons: the existence of two different and independent flow rates at each phase, five or more possible flow patterns, different fluid velocities at the phases, and sometimes a non-Newtonian associated behavior, due to the formation of an oil-water emulsion. There are two main groups for leak detection techniques: the models (or CPM, as stated in [API_1130]) which monitor the flow in real time (CVB, RTTM, PPA, etc.) from inside the pipeline (the instrument sensor is actually in physical contact with the fluid), and try to model the flow using a state estimator; and those based on dedicated external sensors (thermal, mass dispersion, etc) along the pipeline. Most of the technologies at the first group rely entirely on volumetric flow rate measurements, which turn them quite ineffective for multiphase flow. It is also relevant to consider that in some multiphase flow pipelines, the flow pattern changes quite random and intensively, allowing from a bubble pattern, to a slug pattern. There is sometimes the situation where a gas slug is big enough to fill entirely a short line and allow it to behave similarly to a gas pipeline, during a certain time (in fact, this was the case of one of the field tests this work will describe). This will bring unpredictability to those lines, in opposition to a regular single-phase line. Within this frame, the systems based on prediction approaches (hydraulic, statistical, etc, i. e., CPM’s), will show a good probability to be unreliable, inaccurate and not sensitive. The acoustic system is an exception to those two groups of technologies previously mentioned. It has, on one hand, a sensor that really touches the fluid (which would suggest it to be within the first group), but there’s no flow model behind it, on the other hand, but an acoustic sign analysis algorithm, acting somewhat like a piece of hardware. This paper will describe, discuss and report data for tests using an acoustic leak detection system at three different multiphase flow pipelines in Brazil, managed by PETROBRAS Production & Exploration Department.
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Pei, Shengyu, Lang Tong, Xia Li, Jin Jiang, and Jingyu Huang. "Feed-forward network for cancer detection." In 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2017. http://dx.doi.org/10.1109/fskd.2017.8393356.

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Gkizeli, Maria, and George N. Karystinos. "Noncoherent Detection in Amplify-and-Forward Relay Systems." In IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference. IEEE, 2008. http://dx.doi.org/10.1109/glocom.2008.ecp.193.

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Zhang, Keke, Xueyong Zheng, Xingkui Yan, Shizhe Chen, Xiaozheng Wan, Jiming Zhang, Qiang Zhao, Bo Wang, and Huanyu Zhao. "Research on visibility detection based on forward scattering technology." In Advanced Sensor Systems and Applications IX, edited by Tiegen Liu, Gang-Ding Peng, and Zuyuan He. SPIE, 2019. http://dx.doi.org/10.1117/12.2540728.

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Hou, Weikun, Xianbin Wang, and Ahmed Refaey. "Misbehavior detection in amplify-and-forward cooperative OFDM systems." In ICC 2013 - 2013 IEEE International Conference on Communications. IEEE, 2013. http://dx.doi.org/10.1109/icc.2013.6655437.

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Lingjia Gu, Shuxu Guo, Ruizhi Ren, and Shuang Zhang. "Iterative detection for differential decode-and-forward cooperative communication." In 2007 5th International Conference on Communications, Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/icccas.2007.4348160.

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Ning Wei, Weixin Liu, Zhongpei Zhang, and Shaoqian Li. "Iterative detection for differential decode-and-forward cooperative communication." In 2007 5th International Conference on Communications, Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/icccas.2007.6250078.

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Mostafa, H., M. Marey, M. Ahmed, and O. Dobre. "Detection Techniques for Two-Relays Decode and Forward Cooperative Systems." In 2011 IEEE Global Communications Conference (GLOBECOM 2011). IEEE, 2011. http://dx.doi.org/10.1109/glocom.2011.6133833.

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de Wit, J. J. M., and W. L. van Rossum. "Forward scatter radar for detection of moving people inside buildings." In International Conference on Radar Systems (Radar 2017). Institution of Engineering and Technology, 2017. http://dx.doi.org/10.1049/cp.2017.0399.

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Takizawa, Kenichi, Huan-Bang Li, and Ryuji Kohno. "Precise Leading Edge Detection using a Forward Error Correction Coding." In 2006 3rd International Symposium on Wireless Communication Systems. IEEE, 2006. http://dx.doi.org/10.1109/iswcs.2006.4362398.

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Reports on the topic "Forward detection systems"

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Schmitigal, Joel. Evaluation of Particle Counter Technology for Detection of Fuel Contamination Detection Utilizing Advanced Aviation Forward Area Refueling System. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada597855.

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Patwa, Abid Mahmood. The Forward preshower system and a study of the $J/\psi$ trigger with the D0 detector. Office of Scientific and Technical Information (OSTI), January 2002. http://dx.doi.org/10.2172/1420962.

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