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Tree-Based Vehicle Classification System 14

Tree-Based Vehicle Classification System

引用

2017 14th International conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Saripan, Kiatkachorn Nuthong, Chaiwat King Mongkuts Inst Technol Ladkrabang Int Coll Bangkok Thailand

ISBN: (纸本)9781538604496

Nowadays, traffic surveillance systems are installed in major cities. They are usually used for two purposes, i.e. real-time traffic monitoring and archived events searching. For the latter purpose, the traffic surveillance systems can be used for police officers' benefits, such as vehicle identification in specific events including stolen vehicles or hit-and-run cases. In such circumstances, the officers are required to identify the vehicle in archived videos according to its appearances. This task is usually accomplished manually through visual perception. The problems arise from this approach Even though this approach results in good accuracy, it is time consuming and prone to error due to human fatigue for long duration videos. In order to solve these problems, a tree based vehicle classification system is proposed. This system consists of three modules, i.e. feature extraction, classification, and search manager. The feature extraction module is used for image and video processing. It extracts the desired features to be used further in the classification module. The classification module uses these features and results in pre-defined vehicle classes. The classification results are stored in the search manager module for further filtering according to user's query command. This paper focuses on the classification module. There are two features designed to be used in the proposed classification module, i.e. types and colors. Vehicles are classified into four classes of type and seven classes of color. Several tree based algorithms are applied to the dataset. The experimental results show that all the algorithms are comparable. However, the highest accuracy for type and color classification are obtained by using decision tree and bagged decision tree, respectively.

关键词： Decision trees Videos Feature extraction Color Training image color analysis Bagging

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Multi-functional informational - instrumental technology for the hydrochemical monitoring 21

Multi-functional informational - instrumental technology for...

引用

21st International conference on Control systems and Computer Science (CSCS)

作者： Nitu, Costica Dobrescu, Anda Sabena Krapivin, Vladimir F. Mkrtchyan, Ferdenant A. Soldatov, Vladimir Yu Univ Politehn Bucuresti Bucharest Romania Russian Acad Sci Kotelnikov Inst Radioengn & Elect Moscow Russia

ISBN: (纸本)9781538618394

Water quality operative control is considered when chemical analysis is possible. In this paper, new information-instrumental technology is proposed. This technology is based on combined use of optical instrumental means and recognition algorithms of spectral images. Adaptive multi-functional system is proposed to be as tool for operative diagnosis of hydrochemical processes. This system has two levels of items that realize specific functions of monitoring data analysis and processing. The system measuring functions are based on spectroellipsometric technology. Examples of the system use are given.

关键词： water quality monitoring diagnostics algorithm spectroellipsometer image recognition

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Weed Segmentation from Grayscale Tobacco Seedling images 25th

Weed Segmentation from Grayscale Tobacco Seedling Images

引用

25th International conference on Robotics in Alpe-Adria-Danube Region (RAAD)

作者： Lameski, Petre Zdravevski, Eftim Kulakov, Andrea Univ St Cyril & Methodius Skopje Fac Comp Sci & Engn Skopje North Macedonia

ISBN: (纸本)9783319490588;9783319490571

Manual weed extraction from young seedlings is a hard manual labour process. It has to be continuously performed to increase the yield per land unit of any agricultural product. Precise segmentation of plant images is an important step towards creating a camera sensor for weed detection. In this paper we present a machine learning approach for segmenting weed parts from images. A dataset has been generated using bumblebee camera under various light conditions and subsequently training and test patches were extracted. We have generated various texture-based descriptors and used different classification algorithms aiming at correctly recognizing weed patches. The results show that in a case when the images are grayscale, the light conditions are varying, and the distance of the camera to the weeds is not constant machine learning algorithms perform poorly.

关键词： Weed control image processing Machine learning Precision agriculture

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VBII-UAV: Vision-Based Infrastructure Inspection-UAV 5th

VBII-UAV: Vision-Based Infrastructure Inspection-UAV

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5th World conference on Information systems and Technologies (WorldCIST)

作者： Al-Kaff, Abdulla Miguel Moreno, Francisco San Jose, Luis Javier Garcia, Fernando Martin, David de la Escalera, Arturo Nieva, Alberto Meana Garcea, Jose Luis Univ Carlos III Madrid Intelligent Syst Lab Ave Univ 30 Madrid 28911 Spain COPISA Integrated Serv Barcelona Spain

ISBN: (纸本)9783319565385;9783319565378

Unmanned Aerial Vehicles (UAV) have the capabilities to undertake tasks in remote, dangerous and dull situations. One of these situations is the infrastructure inspection, at which, using the UAV decreases the risk and the operation time of the task comparing to a human inspector. Therefore, this paper presents a small vision-based UAV with the capability of inspection tasks of a civil and industrial infrastructure. The presented system is divided into three main algorithms;Depth-Color image correlation, Plane segmentation and distance estimation and Visual servoing. The system has been validated with real flight tests, and the obtained results show the accuracy of the system in both inspection measurements and the UAV maneuver controlling.

关键词： Inspection UAV Computer vision Visual servoing

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Proceedings - 2017 International conference on Promising Electronic Technologies, ICPET 2017

Proceedings - 2017 International Conference on Promising Ele...

引用

2017 International conference on Promising Electronic Technologies, ICPET 2017

ISBN: (纸本)9781538622698

The proceedings contain 25 papers. The topics discussed include: sizing and simulation of an energy sufficient stand-alone PV pumping system;mobile educational workbench for classical and programmable control applications;fuzzy gain scheduling control for a special case of 2nd order non-linear systems;detection and removing cross site scripting vulnerability in PHP web application;mobile-computing based rationalization for energy consumption;design of efficient microstrip linear antenna array for 5G communications systems;and intelligent maze solving robot based on image processing and graph theory algorithms.

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Smart Annotation Tool for Multi-sensor Gait-based Daily Activity Data

Smart Annotation Tool for Multi-sensor Gait-based Daily Acti...

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IEEE International conference on Pervasive Computing and Communications

作者： Christine F. Martindale Nils Roth Julius Hannink Sebastijan Sprager Bjoern M. Eskofier Machine Learning and Data Analytics Lab Computer Science Department Friedrich-Alexander University Erlangen-Nürnberg Germany Faculty of Computer and Information Science University of Ljubljana Slovenia

ISBN: (纸本)9781538632284

The monitoring of patients within a natural, home environment is important in order to close knowledge gaps in the treatment and care of neurodegenerative diseases, such as quantifying the daily fluctuation of Parkinson's patients' symptoms. The combination of machine learning algorithms and wearable sensors for gait analysis is becoming capable of achieving this. However, these algorithms require large, labelled, realistic datasets for training. Most systems used as a ground truth for labelling are restricted to the laboratory environment, as well as being large and expensive. We propose a study design for a realistic activity monitoring dataset, collected with inertial measurement units, pressure insoles and cameras. It is not restricted by a fixed location or capture volume and still enables the labelling of gait phases or, where non-gait movement such as jumping occur: on-the-ground, off-the-ground phases. Additionally, this paper proposes a smart annotation tool which reduces annotation cost by more than 80%. This smart annotation is based on edge detection within the pressure sensor signal. The tool also enables annotators to perform assisted correction of these labels in a post-processing step. This system enables the collection and labelling of large, fairly realistic datasets where 93% of the automatically generated labels are correct and only an additional 10% need to be inserted manually. Our tool and protocol, as a whole, will be useful for efficiently collecting the large datasets needed for training and validation of algorithms capable of cyclic human motion analysis in natural environments.

关键词： image edge detection Tools Cameras Labeling Pressure sensors Intelligent sensors Edge detection Pressure Sensor Device Component Cameras intelligent sensors ANNOTATIONS laboratory environment Dataset Wearable sensors Measurement units Research Design INSOLE Packaging

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Predictor-Based controllers for UAVs with input delay

Predictor-Based controllers for UAVs with input delay

引用

IEEE International conference on Advanced Intelligent Mechatronics (AIM)

作者： Cao, Ning Lynch, Alan F. Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada

ISBN: (纸本)9781509060009

This paper proposes predictor-based controllers for a class of systems with input delay and which relate to the control of Unmanned Aerial Vehicles (UAVs). The first control problem considered is motion control where position of the vehicle is regulated to a constant. The second problem arises from visual servoing where camera measurements are used to control the vehicle's relative pose to a visual target. The UAV control is assumed to have an inner-outer loop structure with the delay appearing only in the outer loop variables. In the visual servoing case, a projection-based adaptive law is developed since depth information cannot be determined from the image of a single camera. Sufficient conditions in form of linear matrix inequalities (LMIs) are given for global asymptotic stability of the outer-loop.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Evaluating classification algorithms for improved wastewater system calibration 15

Evaluating classification algorithms for improved wastewater...

引用

15th International conference on Computing and Control for the Water Industry, CCWI 2017

作者： Younis, Mohammed Chachan Keedwell, Edward Savic, Dragan Raine, Anthony Department of Computer Science Centre for Water Systems College of Engineering Physics and Mathematics University of Exeter United Kingdom WEM MCIWEM Pell Frischmann

Hydraulic models provide an approximate model of rainfallcollection (storm), wastewatercollection (foul), and combined (both rainfall and wastewater collections) network performance, capturing the large scale element of the system, but such systems require calibration with real world data to achieve reliable and accurate results. However, many factors surrounding real-world network and catchment characteristics are unknown and can influence the hydraulic performance of the network. Consequently, calibrating wastewater models to accurately reflect real-world conditions is a time consuming and complex process. This paper employs a two stage urban run offforecasting approach with a combination of image classification techniques and modelling using Info Works ICM. The image classification section consists of the automated processing of the satellite image as an aid to modelling wastewater in the urban environment by classifying the land-cover as pervious and impervious segments of water from rainfall events. By classifying such areas with an urban catchment, and by using the Wallingford PR Equation across all testsof Area 1 (roads), 2 (roofs) and 3 (permeable area), we explore the potential for a partially automated network system calibration processof a wastewater network. © 2020 CCWI 2017 - 15th International conference on Computing and Control for the Water Industry. All rights reserved.

关键词： image classification

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Advances in Rough Set Based Hybrid Approaches for Medical image Analysis

Advances in Rough Set Based Hybrid Approaches for Medical Im...

引用

International Joint conference on Rough Sets (IJCRS)

作者： Maji, Pradipta Indian Stat Inst Biomed Imaging & Bioinformat Lab Machine Intelligence Unit 203 BT Rd Kolkata W Bengal India

ISBN: (纸本)9783319608372;9783319608365

Recent advancement in the area of medical imaging produces a huge amount of image data. Automatic extraction of meaningful information from these data has become necessary. In this regard, different image processing techniques provide efficient tools to extract and interpret meaningful information from the medical images, which, in turn, provide valuable directions for medical diagnosis. One of the major problems in real-life medical image data analysis is uncertainty. Among other soft computing techniques, rough sets provide a powerful tool to handle uncertainties, vagueness, and incompleteness associated with data, while fuzzy set and probabilistic paradigm serve as analytical tools for dealing with uncertainty that arises due to the overlapping characteristics and/or randomness in data. Hence, they can be integrated judiciously to develop efficient algorithms for automatic analysis of medical image data. In this regard, the paper presents a brief review on recent advances of rough set based hybrid intelligent approaches for medical image analysis.

关键词： Rough sets Medical imaging Hybrid intelligent systems

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Face Presentation Attack Detection by Exploring Spectral Signatures 30

Face Presentation Attack Detection by Exploring Spectral Sig...

引用

30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Raghavendra, R. Raja, Kiran B. Venkatesh, Sushma Busch, Christoph NTNU Norwegian Biometr Lab Gjovik Norway

ISBN: (纸本)9781538607336

Presentation attack on the face recognition systems is well studied in the biometrics community resulting in various techniques for detecting the attacks. A low-cost presentation attack (e.g. print attacks) on face recognition systems has been demonstrated for systems operating in visible, multispectral (visible and near infrared spectrum) and extended multispectral (more than two spectral bands spanning from visible to near infrared space, commonly in 500nm-1000nm). In this paper, we propose a novel method to detect the presentation attacks on the extended multispectral face recognition systems. The proposed method is based on characterising the reflectance properties of the captured image through the spectral signature. The spectral signature is further classified using the linear Support Vector Machine (SVM) to obtain the decision on presented sample as an artefact or bona-fide. Since the reflectance property of the human skin and the artefact material differ, the proposed method can efficiently detect the presentation attacks on the extended multispectral system. Extensive experiments are carried out on a publicly available extended multispectral face database (EMSPAD) comprised of 50 subjects with two different Presentation Attack Instruments (PAI) generated using two different printers. The comparison analysis is presented by comparing the performance of the proposed scheme with the contemporary schemes based on the image fusion and score level fusion for PAD. Based on the obtained results, the proposed method has indicated the best performance in detecting both known and unknown attacks.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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