Relevant bibliographies by topics / Image monitoring system

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Image monitoring system'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Image monitoring system"

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Muhadi, Nur, Ahmad Abdullah, Siti Bejo, Muhammad Mahadi, and Ana Mijic. "Image Segmentation Methods for Flood Monitoring System." Water 12, no. 6 (2020): 1825. http://dx.doi.org/10.3390/w12061825.

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Flood disasters are considered annual disasters in Malaysia due to their consistent occurrence. They are among the most dangerous disasters in the country. Lack of data during flood events is the main constraint to improving flood monitoring systems. With the rapid development of information technology, flood monitoring systems using a computer vision approach have gained attention over the last decade. Computer vision requires an image segmentation technique to understand the content of the image and to facilitate analysis. Various segmentation algorithms have been developed to improve result
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Hegde, Mahesh Subray, and Dr Ramakanth Kumar P. "Server Room Monitoring System using CCTV." International Journal of Innovative Technology and Exploring Engineering 11, no. 9 (2022): 18–22. http://dx.doi.org/10.35940/ijitee.g9211.0811922.

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Server Room is the main part when it comes to any organization since any malicious activity in the server room may bring down the whole server room bringing the work of organization to halt. Hence, we need a server room monitoring system which works on real time images and monitors using compressed circuit television (CCTV). The framework used for server room monitoring is YOLO (You Only look Once). YOLO employs Convolutional neural networks (CNN) for image processing. In CNN image must pass through different layers like Convolutional layer, pooling layer, ReLu layer and fully connected layer.
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Mahesh, Subray Hegde, and Ramakanth Kumar P. Dr. "Server Room Monitoring System using CCTV." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 11, no. 9 (2023): 18–22. https://doi.org/10.35940/ijitee.G9211.0811922.

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<strong>Abstract</strong>: Server Room is the main part when it comes to any organization since any malicious activity in the server room may bring down the whole server room bringing the work of organization to halt. Hence, we need a server room monitoring system which works on real time images and monitors using compressed circuit television (CCTV). The framework used for server room monitoring is YOLO (You Only look Once). YOLO employs Convolutional neural networks (CNN) for image processing. In CNN image must pass through different layers like Convolutional layer, pooling layer, ReLu layer
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Bao, Kongjun, and Yaoxi Bao. "Image Processing Technology in Remote Monitoring and Intelligent Medical System." Journal of Healthcare Engineering 2021 (November 22, 2021): 1–6. http://dx.doi.org/10.1155/2021/6549891.

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In order to study the application of image processing technology in remote monitoring and intelligent medical systems, the principle and implementation method of a remote intelligent image monitoring system based on virtual local area network is proposed; this method analyzes the key technologies to be considered in the remote realization of image monitoring, adopts advanced digital image compression coding and decoding technology and digital image transmission technology, and applies intelligent image processing and recognition technology to display, adjust, and track images; it overcomes the
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V, Dr Radhika. "IoT based Automatic Classroom Attendance Monitoring System Using Image Processing." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (2020): 2873–77. http://dx.doi.org/10.5373/jardcs/v12sp7/20202429.

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Li, Xiao Ling. "Forest Fire Monitoring System Based on Image Analysis." Advanced Materials Research 267 (June 2011): 155–59. http://dx.doi.org/10.4028/www.scientific.net/amr.267.155.

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Large forest fires are very hazardous and often cause greater losses. However, due to the vast coverage of forests and the environmental complexity, monitoring which relies on sensor detection of direct contact almost cannot achieve its monitoring function. In this paper, the author proposes that long-range images will first be acquired and so do the images of a larger dynamic range of the observed region, then an embedded video monitoring system will be formed realizing a dynamic monitoring. With the techniques of dynamic image analysis and processing, dynamic image alarms and control signals
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Zhang, Xiaomin, Yanning Zhang, Jinfeng Geng, Jinming Pan, Xinyao Huang, and Xiuqin Rao. "Feather Damage Monitoring System Using RGB-Depth-Thermal Model for Chickens." Animals 13, no. 1 (2022): 126. http://dx.doi.org/10.3390/ani13010126.

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Feather damage is a continuous health and welfare challenge among laying hens. Infrared thermography is a tool that can evaluate the changes in the surface temperature, derived from an inflammatory process that would make it possible to objectively determine the depth of the damage to the dermis. Therefore, the objective of this article was to develop an approach to feather damage assessment based on visible light and infrared thermography. Fusing information obtained from these two bands can highlight their strengths, which is more evident in the assessment of feather damage. A novel pipeline
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Argade, Ruchika, Mayuri Dengale, Snehal Jagtap, and Prof Patharwalkar Shilpa s. "Leather Monitoring System Using Image Processing." IOSR journal of VLSI and Signal Processing 4, no. 2 (2014): 09–12. http://dx.doi.org/10.9790/4200-04220912.

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Haryanto, Desi Anis Anggraini, Miftachul Ulum, and Achmad Fiqhi Ibadillah. "Image Processing Based Aquaponics Monitoring System." JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) 5, no. 1 (2021): 37–59. http://dx.doi.org/10.21070/jeeeu.v5i1.1220.

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Aquaponics means a culture that is very necessary to be applied, because in this system it is a combination of fish farming techniques as well as plant enlargement techniques by hydroponics. This research develops a smart aquaponics system that can control and increase the acidity level, air temperature, fish feed, and the installation of a camera to monitor fish development. In this system, there are sensors installed to retrieve data. Thus, air quality and circulation is well maintained. The results obtained from this study are to test an automatic feed system that runs well for each experim
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Sari, Dewi Mutiara, Bayu Sandi Marta, Muhammad Amin A, and Haryo Dwito Armono. "The Analysis of Underwater Imagery System for Armor Unit Monitoring Application." International Journal of Artificial Intelligence & Robotics (IJAIR) 5, no. 1 (2023): 1–12. http://dx.doi.org/10.25139/ijair.v5i1.5918.

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The placement of armor units for breakwaters in Indonesia is still done manually, which depends on divers in each placement of the armor unit. The use of divers is less effective due to limited communication between divers and excavator operators, making divers in the water take a long time. This makes the diver's job risky and expensive. This research presents a vision system to reduce the diver's role in adjusting the position of each armor unit. This vision system is built with two cameras connected to a mini-computer. This system has an image improvement process by comparing three methods.
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Dissertations / Theses on the topic "Image monitoring system"

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Rizzo, Benjamin. "Laser monitoring system for the ALICE ITS." Click here for online access in Bluebrary, 2008. http://hdl.handle.net/10504/109.

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Nordin, Md Jan. "An image reconstruction algorithm for a dual modality tomographic system." Thesis, Sheffield Hallam University, 1995. http://shura.shu.ac.uk/20268/.

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This thesis describes an investigation into the use of dual modality tomography to measure component concentrations within a cross-section. The benefits and limitations of using dual modality compared with single modality are investigated and discussed. A number of methods are available to provide imaging systems for process tomography applications and seven imaging techniques are reviewed. Two modalities of tomography were chosen for investigation (i.e. Electrical Impedance Tomography (EIT) and optical tomography) and the proposed dual modality system is presented. Image reconstruction algori
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Utami, Dian Wahyu. "Visual simulation of Brisbane River-Moreton Bay System in a decision framework environment /." St. Lucia, Qld, 2002. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe17279.pdf.

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Villalobos, Gregorio. "Food Image Processing for a Semi-Automatic Nutrient Intake Monitoring System." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/20698.

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According to the World Health Organization (WHO) statistics, obesity has reached epidemic proportions, with over 1.5 billion adults suffering from overweight reported in 2008. As obesity and overweight are major risks to human health, obesity treatment has been the focus of a large number of recent studies. Obesity treatment requires constant monitoring of the patient’s diet. The smart technologies of today’s intelligent environment can be used for the development of appropriate monitoring systems for obesity treatment. In this thesis, we propose a smart system that takes advantage of smartpho
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Norcliffe, Brian Andrew Woodfield. "A study of a digital image based monitoring system for slopes." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq20684.pdf.

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Ceco, Ema. "Image Analysis in the Field of Oil Contamination Monitoring." Thesis, Linköpings universitet, Datorseende, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68750.

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Monitoring wear particles in lubricating oils allows specialists to evaluate thehealth and functionality of a mechanical system. The main analysis techniquesavailable today are manual particle analysis and automatic optical analysis. Man-ual particle analysis is effective and reliable since the analyst continuously seeswhat is being counted . The drawback is that the technique is quite time demand-ing and dependent of the skills of the analyst. Automatic optical particle countingconstitutes of a closed system not allowing for the objects counted to be observedin real-time. This has resulted in
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Sánchez, García Elena. "Photogrammetry and image processing techniques for beach monitoring." Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/123956.

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[ES] Las playas son ambientes ecológicos sumamente valiosos donde a lo largo de una frágil franja de transición converge el entorno terrestre y el medio marino. Durante el último siglo, la mejora en la comprensión de los procesos físicos que ocurren en la zona costera se ha convertido en un asunto de máxima importancia. Para abordar una planificación coherente de la gestión costera se requiere tomar en consideración el dinamismo de los diferentes cambios morfológicos que caracterizan estos ambientes a distintas escalas espaciales y temporales. El límite tierra-agua varía en función de la posi
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Hockey, Andrew. "Computational modelling of the language production system : semantic memory, conflict monitoring, and cognitive control processes /." [St. Lucia, Qld.], 2006. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe20099.pdf.

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Cooke, HBM. "Applying Expert System Technology in a Distributed Monitoring System: An Efficient Response Mechanism for Unknown Threats." Thesis, Honours thesis, University of Tasmania, 2005. https://eprints.utas.edu.au/245/1/Final_Thesis.pdf.

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Detecting unknown threats is a paradox; how do you detect a threat if it is not known to exist? The answer is that unknown threat detection is the process of making a previously unknown threat identifiable in the shortest possible time frame. This thesis examines the possibility of creating an unknown threat detection mechanism that security experts can use for developing a flexible protection system for networks. A system that allows the detection of unknown threats through distributed host based monitoring and the incorporation of dynamic and flexible logics with situational knowledge is des
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Jeunnette, Mark N. (Mark Nathaniel) 1979. "Airborne monitoring system for in-season agriculture : operational considerations and image processing for wide-area sensing." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122885.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 123-127).<br>Remote sensing, in particular multispectral imagery, can measure crop health and detect in-season disturbances such as pests and diseases before they are visible to the naked eye, but it is inaccessible to small-plot farmers, especially in developing countries. So-called eExtension services provide up-to-date, reliable information for small-plot farmers, but struggle to collect the plot-specific cro
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Books on the topic "Image monitoring system"

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Marwala, Tshilidzi. Condition Monitoring Using Computational Intelligence Methods: Applications in Mechanical and Electrical Systems. Springer London, 2012.

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Marwala, Tshilidzi. Condition Monitoring Using Computational Intelligence Methods: Applications in Mechanical and Electrical Systems. Springer London, 2012.

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Haines, Richard F. Television image compression and small animal remote monitoring. Research Institute for Advanced Computer Science, 1990.

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J, Peters Kara, Society of Photo-optical Instrumentation Engineers., American Society of Mechanical Engineers., Intelligent Materials Forum (Mitō Kagaku Gijutsu Kyōkai), Jet Propulsion Laboratory (U.S.), and National Science Foundation (U.S.), eds. Sensor systems and networks: Phenomena, technology, and applications for NDE and health monitoring 2007. SPIE, 2007.

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Helena, Mitasova, ed. Open source GIS: A GRASS GIS approach. 3rd ed. Springer, 2008.

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Helena, Mitasova, ed. Open source GIS: A GRASS GIS approach. 2nd ed. Kluwer Academic Publishers, 2004.

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Huang, Yongru. A digital photogrammetry system for industrial monitoring (UNISURV report). School of Geomatic Engineering, University of New South Wales, 1997.

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Traffic Monitoring and Analysis Lecture Notes in Computer Science Computer Communication N. Springer, 2011.

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Ince, Can, and Alexandre Lima. Monitoring the microcirculation in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0142.

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The microcirculation is the key physiological compartment of the cardiovascular system where oxygen is delivered by convection and diffusion to respiring parenchymal cells to support cellular, and thereby organ, function. The microcirculation consists of microvessels less than 100 µmin diameter consisting of arterioles, capillaries, and venules. The smallest vessels (&lt;6 µm) are the capillaries where most oxygen leaves the circulation by passive diffusion to cells. The critical role of the microcirculation has long been recognized, although it has recently been possible to image its function
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Acharjee, Suvojit, Nilanjan Dey, and Amira Ashour. Applied Video Processing in Surveillance and Monitoring Systems. IGI Global, 2016.

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Book chapters on the topic "Image monitoring system"

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Zala, Bhagyashree, Ritik Gandhi, Fan Yang, Tiago Valente, and Irene Cheng. "Image Based Cattle Monitoring System." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82475-3_14.

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Rodríguez, Germán, Maria Fuciños, Xosé M. Pardo, and Xosé R. Fdez-Vidal. "Videogrammetry System for Wind Turbine Vibration Monitoring." In Pattern Recognition and Image Analysis. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19390-8_57.

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Batista, Jorge P. "A Real-Time Driver Visual Attention Monitoring System." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492429_25.

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Chu, Yi, Guohai Liu, Congli Mei, and Yuhan Ding. "Dust Monitoring System Based on Video Image Processing." In Electrical, Information Engineering and Mechatronics 2011. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2467-2_92.

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Alfarizal, Niksen, Iskandar Lutfi, Nyayu Latifah Husni, et al. "Moslem Prayer Monitoring System Based on Image Processing." In Atlantis Highlights in Engineering. Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-118-0_50.

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Yang, E., Jing Yang, Kangyan Zeng, and Yan Zheng. "Construction Safety Monitoring System Based on UAV Image." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28867-8_40.

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Saboune, Jamal, Mehdi Arezoomand, Luc Martel, and Robert Laganiere. "A Visual Blindspot Monitoring System for Safe Lane Changes." In Image Analysis and Processing – ICIAP 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24088-1_1.

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Lee, Jiann-Der, Jiann-Der Li, Li-Chang Liu, and Chi-Ming Chen. "A Novel Driving Pattern Recognition and Status Monitoring System." In Advances in Image and Video Technology. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11949534_50.

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Torcinovich, Alessandro, Marco Fratton, Marcello Pelillo, Alberto Pravato, and Alessandro Roncato. "A Computer Vision System for Monitoring Ice-Cream Freezers." In Image Analysis and Processing - ICIAP 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68548-9_31.

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Gamboa, Hugo, and Ana Fred. "A User Authentication Technic Using a~Web Interaction Monitoring System." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44871-6_29.

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Conference papers on the topic "Image monitoring system"

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P, Baby Shamini, Kalaivani B, Kasu Manaswi, Kantabathina Tejaswini, Nellepalli Pavithra, and Kalikiri Sindhu. "Agricultural Monitoring System Using Image Recognition." In 2024 International Conference on Control, Computing, Communication and Materials (ICCCCM). IEEE, 2024. https://doi.org/10.1109/iccccm61016.2024.11039874.

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Wang, Yinghong, Ming Li, Fanglin Chen, Jun Xu, and Guangming Lu. "An Image Based Automatic Water Level Monitoring System." In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2024. https://doi.org/10.1109/icaice63571.2024.10864180.

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Shri, A. Lekha, R. R. Swathiha, M. Mohamed Ismail, M. Krithiga, B. Meenakshi, and M. Kathir. "IoT-Enhanced Forest Fire Monitoring and Notification System." In 2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN). IEEE, 2024. http://dx.doi.org/10.1109/icipcn63822.2024.00148.

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Lu, Ming-Chih, Tien-Yu Tang, Cheng-Pei Tsai, Wei-Yen Wang, and I.-Hsum Li. "Image-based landslide monitoring system." In 2011 International Conference on System Science and Engineering (ICSSE). IEEE, 2011. http://dx.doi.org/10.1109/icsse.2011.5961981.

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SEO, JUNWON, EUISEOK JEONG, and JAMES P. WACKER. "UAS INSPECTION IMAGE ENHANCEMENT COUPLED WITH DENOISE ALGORITHM BASED ON DEEP NEURAL NETWORK." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36333.

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Unmanned Aerial System (UAS) technologies integrated with image processing algorithms are considered timely and useful for bridge inspections because of improved accessibility, recording ability, and cost-efficiency compared to the conventional inspection approach. The image processing algorithms can improve the ability of the UAS-aided bridge inspections in efficiently identifying and quantifying deterioration. This study was aimed to inspect an in-service single-span precast concrete bridge on a rural roadway in South Dakota using UAS technologies coupled with a Deep Neural Network (DNN) den
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Hasan, Md Mahmud-Ul, Md Kafiul Islam, Mehedi Azad Shawon, and Tasnuva Faruk Nowrin. "Embedded programmable blood pressure monitoring system." In Second International Conference on Digital Image Processing. SPIE, 2010. http://dx.doi.org/10.1117/12.855047.

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Ivanov, Eugenyi, Wolfgang Osten, and Werner P. O. Jueptner. "Image processing system for monitoring of conveyor belt systems." In IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, edited by Benjamin M. Dawson, Stephen S. Wilson, and Frederick Y. Wu. SPIE, 1994. http://dx.doi.org/10.1117/12.171219.

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feng, cong, Yuanyuan Li, Xinjun Ma, and Chenchen Wu. "Fisheye camera around view monitoring system." In Ninth International Conference on Graphic and Image Processing, edited by Hui Yu and Junyu Dong. SPIE, 2018. http://dx.doi.org/10.1117/12.2302926.

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Freitass, Charles N. C., Filipe R. Cordeiro, and Adenilton J. Da Silva. "Food Recognition System for Nutrition Monitoring." In XV Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/eniac.2018.4415.

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This research consists of the analysis of the methods of image recognition, focusing on the problem of food classification, aiming to use the methods in a mobile application for the assistance in food monitoring and control. Thus, the development of the work contemplates the use of the deep learning method, focused on the recognition of food in images, with the use of neural convolution networks (CNN). For this purpose, a data set consisting of more than 1000 images and 5 food classes was constructed in order to simulate the SimpleNet, MiniVGGNet and Small Xception models, and thus define a le
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Illig, David W., and Linda Mullen. "Image processing technique for an underwater modulated pulse laser imaging system." In Ocean Sensing and Monitoring X, edited by Weilin "Will" Hou and Robert A. Arnone. SPIE, 2018. http://dx.doi.org/10.1117/12.2309569.

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Reports on the topic "Image monitoring system"

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Conery, Ian, Brittany Bruder, Connor Geis, Jessamin Straub, Nicholas Spore, and Katherine Brodie. Applicability of CoastSnap, a crowd-sourced coastal monitoring approach for US Army Corps of Engineers district use. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47568.

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This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details the pilot deployment, accuracy evaluation, and best practices of the citizen-science, coastal-image monitoring program CoastSnap. Despite the need for regular observational data, many coastlines are monitored infrequently due to cost and personnel, and this cell phone-image-based approach represents a new potential data source to districts in addition to providing an outreach opportunity for the public. Requiring minimal hardware and signage, the system is simple to install but re
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Mazari, Mehran, Yahaira Nava-Gonzalez, Ly Jacky Nhiayi, and Mohamad Saleh. Smart Highway Construction Site Monitoring Using Artificial Intelligence. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2336.

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Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes.
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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, 2023. http://dx.doi.org/10.3289/sw_2_2023.

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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in
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Panta, Manisha, Padam Thapa, Md Hoque, et al. Application of deep learning for segmenting seepages in levee systems. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49453.

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Seepage is a typical hydraulic factor that can initiate the breaching process in a levee system. If not identified and treated on time, seepages can be a severe problem for levees, weakening the levee structure and eventually leading to collapse. Therefore, it is essential always to be vigilant with regular monitoring procedures to identify seepages throughout these levee systems and perform adequate repairs to limit potential threats from unforeseen levee failures. This paper introduces a fully convolutional neural network to identify and segment seepage from the image in levee systems. To th
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Falconer, David G. L51774 Remote Sensing of Hazardous Ground Movement about Buried Gas Transmission Lines. Pipeline Research Council International, Inc. (PRCI), 1997. http://dx.doi.org/10.55274/r0011973.

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Reviews the available sensors for monitoring hazardous ground movement. Our review was limited to airborne and spaceborne sensors for access, performance, and productivity considerations. It was observed that certain ground movement is comparatively localized, e.g., earthquake faulting, while other activity may extend for thousands of kilometers, e.g., frost heave. Accordingly, we have considered two operating modes for the sensor-platform system, namely, site-by-site and continuous corridor. To determine the suitability of the candidate sensors for pipeline monitoring, we have assessed the ex
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Suir, Glenn, Christina Saltus, Charles Sasser, et al. Evaluating drone truthing as an alternative to ground truthing : an example with wetland plant identification. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42201.

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Satellite remote sensing of wetlands provides many advantages to traditional monitoring and mapping methods. However, remote sensing often remains reliant on labor- and resource- intensive ground truth data for wetland vegetation identification through image classification training and accuracy assessments. Therefore, this study sought to evaluate the use of unmanned aircraft system (UAS) data as an alternative or supplement to traditional ground truthing techniques in support of remote sensing for identifying and mapping wetland vegetation.
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Suir, Glenn, Christina Saltus, Charles Sasser, et al. Evaluating drone truthing as an alternative to ground truthing : an example with wetland plant identification. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42201.

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Satellite remote sensing of wetlands provides many advantages to traditional monitoring and mapping methods. However, remote sensing often remains reliant on labor- and resource- intensive ground truth data for wetland vegetation identification through image classification training and accuracy assessments. Therefore, this study sought to evaluate the use of unmanned aircraft system (UAS) data as an alternative or supplement to traditional ground truthing techniques in support of remote sensing for identifying and mapping wetland vegetation.
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Panta, Manisha, Md Tamjidul Hoque, Kendall Niles, Joe Tom, Mahdi Abdelguerfi, and Maik Flanagin. Deep learning approach for accurate segmentation of sand boils in levee systems. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49460.

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Sand boils can contribute to the liquefaction of a portion of the levee, leading to levee failure. Accurately detecting and segmenting sand boils is crucial for effectively monitoring and maintaining levee systems. This paper presents SandBoilNet, a fully convolutional neural network with skip connections designed for accurate pixel-level classification or semantic segmentation of sand boils from images in levee systems. In this study, we explore the use of transfer learning for fast training and detecting sand boils through semantic segmentation. By utilizing a pretrained CNN model with ResNe
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Lasko, Kristofer, and Sean Griffin. Monitoring Ecological Restoration with Imagery Tools (MERIT) : Python-based decision support tools integrated into ArcGIS for satellite and UAS image processing, analysis, and classification. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40262.

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Monitoring the impacts of ecosystem restoration strategies requires both short-term and long-term land surface monitoring. The combined use of unmanned aerial systems (UAS) and satellite imagery enable effective landscape and natural resource management. However, processing, analyzing, and creating derivative imagery products can be time consuming, manually intensive, and cost prohibitive. In order to provide fast, accurate, and standardized UAS and satellite imagery processing, we have developed a suite of easy-to-use tools integrated into the graphical user interface (GUI) of ArcMap and ArcG
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Habib, Ayman, Darcy M. Bullock, Yi-Chun Lin, and Raja Manish. Road Ditch Line Mapping with Mobile LiDAR. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317354.

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Maintenance of roadside ditches is important to avoid localized flooding and premature failure of pavements. Scheduling effective preventative maintenance requires mapping of the ditch profile to identify areas requiring excavation of long-term sediment accumulation. High-resolution, high-quality point clouds collected by mobile LiDAR mapping systems (MLMS) provide an opportunity for effective monitoring of roadside ditches and performing hydrological analyses. This study evaluated the applicability of mobile LiDAR for mapping roadside ditches for slope and drainage analyses. The performance o
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