Gotowa bibliografia na temat „Object Detecting Sensors”
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Artykuły w czasopismach na temat "Object Detecting Sensors"
Jung, Sejung, Won Hee Lee, and Youkyung Han. "Change Detection of Building Objects in High-Resolution Single-Sensor and Multi-Sensor Imagery Considering the Sun and Sensor’s Elevation and Azimuth Angles." Remote Sensing 13, no. 18 (2021): 3660. http://dx.doi.org/10.3390/rs13183660.
Pełny tekst źródłaJeong, Seonghark, Minseok Ko, and Jungha Kim. "LiDAR Localization by Removing Moveable Objects." Electronics 12, no. 22 (2023): 4659. http://dx.doi.org/10.3390/electronics12224659.
Pełny tekst źródłaYoon, Sungan, Ahmad Jalal, and Jeongho Cho. "MODAN: Multifocal Object Detection Associative Network for Maritime Horizon Surveillance." Journal of Marine Science and Engineering 11, no. 10 (2023): 1890. http://dx.doi.org/10.3390/jmse11101890.
Pełny tekst źródłaRakesh, L., V. Priyanka, K. Pavan Kumar, N. Mahesh, and K. Sai Kiran. "Radar Based Object Detection using Ultrasonic Sensor." Journal of Remote Sensing GIS & Technology 8, no. 2 (2022): 7–14. http://dx.doi.org/10.46610/jorsgt.2022.v08i02.002.
Pełny tekst źródłaReda, A. M., N. El-Sheimy, and A. Moussa. "DEEP LEARNING FOR OBJECT DETECTION USING RADAR DATA." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 657–64. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-657-2023.
Pełny tekst źródłaMa, Tian J., and Robert J. Anderson. "Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement." Sensors 23, no. 6 (2023): 3314. http://dx.doi.org/10.3390/s23063314.
Pełny tekst źródłaHahn, Bongsu. "Research and Conceptual Design of Sensor Fusion for Object Detection in Dense Smoke Environments." Applied Sciences 12, no. 22 (2022): 11325. http://dx.doi.org/10.3390/app122211325.
Pełny tekst źródłaSchlemmer, Matthias J., Georg Biegelbauer, and Markus Vincze. "Rethinking Robot Vision – Combining Shape and Appearance." International Journal of Advanced Robotic Systems 4, no. 3 (2007): 29. http://dx.doi.org/10.5772/5691.
Pełny tekst źródłaKasinath, S., S. K. Stephan, Edward Lisha, K.G. Parthive, and R. Remya. "Enhanced Blind Navigation using YOLO and Sensor Fusion." Recent Innovations in Wireless Network Security 7, no. 3 (2025): 1–10. https://doi.org/10.5281/zenodo.15516516.
Pełny tekst źródłaWahyu Rizki Ananda, Abdul Jabbar Lubis, and Ummul Khair. "Implementation of Motion Sensors and Buzzers on Robots to Detect Object Movement." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 2 (2025): 1354–61. https://doi.org/10.59934/jaiea.v4i2.907.
Pełny tekst źródłaRozprawy doktorskie na temat "Object Detecting Sensors"
Fernandes, Rui Miguel Félix. "Object signature in radio frequency." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/13708.
Pełny tekst źródłaSikdar, Ankita. "Depth based Sensor Fusion in Object Detection and Tracking." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1515075130647622.
Pełny tekst źródłaGudipudi, Venkata Naga Manikanta Aditya. "Detection and velocity of a fast moving object." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14400.
Pełny tekst źródłaTun, Min Han. "Virtual image sensors to track human activity in a smart house." Thesis, Curtin University, 2007. http://hdl.handle.net/20.500.11937/904.
Pełny tekst źródłaVenkataraayan, Kavitha. "Multi-wavelength, multi-beam, photonic based sensor for object discrimination and positioning." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2012. https://ro.ecu.edu.au/theses/488.
Pełny tekst źródłaJaved, Omar. "SCENE MONITORING WITH A FOREST OF COOPERATIVE SENSORS." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3448.
Pełny tekst źródłaJiang, Lixing [Verfasser]. "Object Recognition and Saliency Detection for Indoor Robots using RGB-D Sensors / Lixing Jiang." München : Verlag Dr. Hut, 2016. http://d-nb.info/1106593723/34.
Pełny tekst źródłaGiovanelli, Debora. "Electrochemical detection of gases." Thesis, University of Oxford, 2004. http://ora.ox.ac.uk/objects/uuid:fd447153-b6dd-4be1-aae5-4ece5dc36856.
Pełny tekst źródłaLima, João Paulo Silva do Monte. "Object detection and pose estimation from rectification of natural features using consumer RGB-D sensors." Universidade Federal de Pernambuco, 2014. https://repositorio.ufpe.br/handle/123456789/12143.
Pełny tekst źródłaTun, Min Han. "Virtual image sensors to track human activity in a smart house." Curtin University of Technology, School of Computing, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17557.
Pełny tekst źródłaKsiążki na temat "Object Detecting Sensors"
Yuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.
Znajdź pełny tekst źródłaYuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.
Znajdź pełny tekst źródłaUnited States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.
Znajdź pełny tekst źródłaUnited States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.
Znajdź pełny tekst źródłaUnited States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.
Znajdź pełny tekst źródłaKapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.
Znajdź pełny tekst źródłaKapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.
Znajdź pełny tekst źródłaHarmer, Stuart William, Boris Kapilevich, and Nicholas Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2015.
Znajdź pełny tekst źródłaKapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.
Znajdź pełny tekst źródłaKapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.
Znajdź pełny tekst źródłaCzęści książek na temat "Object Detecting Sensors"
Kang, Byungmun, and DaeEun Kim. "Detecting a Sphere Object with an Array of Magnetic Sensors." In From Animals to Animats 15. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97628-0_11.
Pełny tekst źródłaLee, Seungsoo, Seongwoo Son, Pa Pa Win Aung, Minsoo Park, and Seunghee Park. "Deep Learning Based Pose Estimation of Scaffold Fall Accident Safety Monitoring." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.63.
Pełny tekst źródłaLee, Seungsoo, Seongwoo Son, Pa Pa Win Aung, Minsoo Park, and Seunghee Park. "Deep Learning Based Pose Estimation of Scaffold Fall Accident Safety Monitoring." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.63.
Pełny tekst źródłaGamerdinger, Jörg, Georg Volk, Sven Teufel, et al. "Robust Local and Cooperative Perception Under Varying Environmental Conditions." In Cooperatively Interacting Vehicles. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-60494-2_5.
Pełny tekst źródłaZhang, Xinyu, Jun Li, Zhiwei Li, et al. "Multi-Sensor Object Detection." In Multi-sensor Fusion for Autonomous Driving. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3280-1_4.
Pełny tekst źródłaGölz, Jacqueline, and Christian Hatzfeld. "Sensor Design." In Springer Series on Touch and Haptic Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04536-3_10.
Pełny tekst źródłaYoshitake, Hiroshi, Jinyu Gu, and Motoki Shino. "Occluded Area Detection Based on Sensor Fusion and Panoptic Segmentation." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_66.
Pełny tekst źródłaFrintrop, Simone. "6 Sensor Fusion." In VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11682110_6.
Pełny tekst źródłaDong, Lanfang, Jiakui Yu, Jianfu Wang, and Weinan Gao. "Research of a Framework for Flow Objects Detection and Tracking in Video." In Wearable Sensors and Robots. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2404-7_36.
Pełny tekst źródłaCao, Xuyang, Yongchang Hu, Guoyang Xu, Shuai Song, and Xiaochun Tie. "A Machine-Vision-Based Hub Location Detection Technique for Installing Wind Turbines." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_30.
Pełny tekst źródłaStreszczenia konferencji na temat "Object Detecting Sensors"
Meiresone, Pieter, David Van Hamme, and Wilfried Philips. "Event Intensity Decay with Event Cameras for Efficient Object Detection." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784654.
Pełny tekst źródłaShen, Chongqiang, Xiangyun Ren, Dongfang Yang, Yang Chen, Lihong Qiu, and Ke Wang. "Uncertainty-Based Semi-Supervised Object Detection in Autonomous Driving Environment." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784752.
Pełny tekst źródłaLin, Junan, Stefano Maranó, Bruno Arsenali, et al. "Enhancing Port Automation: A Novel Object Detection Pipeline for Container Ship Bays." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784915.
Pełny tekst źródłaKon, Seitaro, and Ryosaku Kaji. "Detection of Hidden non-Metallic Objects Using Electromagnetic Field." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784473.
Pełny tekst źródłaKuroda, Keiichiro, Yudai Morikaku, Yu Osuka, Ryoya Iegaki, Kota Yoshida, and Shunsuke Okura. "Lightweight Object Detection Model for a CMOS Image Sensor with Binary Feature Extraction." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784814.
Pełny tekst źródłaMaktedar, Asrarulhaq, and Mayurika Chatterjee. "Best Practices in Sensor Selection for Object Detection in Autonomous Driving: A Practitioner’s Perspective." In 11th SAEINDIA International Mobility Conference (SIIMC 2024). SAE International, 2024. https://doi.org/10.4271/2024-28-0218.
Pełny tekst źródłaCardwell, D. N., K. S. Chana, and M. T. Gilboy. "The Development and Testing of a Gas Turbine Engine Foreign Object Damage (FOD) Detection System." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23478.
Pełny tekst źródłaCotton, Darryl, Andy Cranny, Neil White, Steve Beeby, and Paul Chappell. "Design and Development of Integrated Thick-Film Sensors for Prosthetic Hands." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58027.
Pełny tekst źródłaKim, Sung Joon, and Ja Choon Koo. "A New Highly Sensitive Dielectric Slip Detection Sensor for a Robotic Operation." In ASME 2017 Conference on Information Storage and Processing Systems collocated with the ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/isps2017-5403.
Pełny tekst źródłaKim, Sung Joon, Jae Young Choi, Hyung Pil Moon, Hyouk Ryeol Choi, and Ja Choon Koo. "Detection of Slippage Using Flexible Tactile Sensor for a Robot Fingertip." In ASME 2016 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/isps2016-9567.
Pełny tekst źródłaRaporty organizacyjne na temat "Object Detecting Sensors"
Clausen, Jay, Vuong Truong, Sophia Bragdon, et al. Buried-object-detection improvements incorporating environmental phenomenology into signature physics. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45625.
Pełny tekst źródłaClausen, Jay, Susan Frankenstein, Jason Dorvee, et al. Spatial and temporal variance of soil and meteorological properties affecting sensor performance—Phase 2. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41780.
Pełny tekst źródłaYan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.
Pełny tekst źródłaClausen, Jay, Rosa Affleck, Christopher Felt, et al. Modernizing environmental signature physics for target detection. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41240.
Pełny tekst źródłaPorcel Magnusson, Cristina. Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles. SAE International, 2021. http://dx.doi.org/10.4271/epr2021002.
Pełny tekst źródłaMcVay, John. Satellite Enveloped with STITCHED Engineering Sensors for Detection of Approaching Objects. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1893245.
Pełny tekst źródłaMusty, Michael, Vuong Truong, Jay Clausen, et al. Thermal infra-red comparison study of buried objects between humid and desert test beds. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45064.
Pełny tekst źródłaDown, Murray. PR686-203903-R02 Ongoing InSAR Geohazard Monitoring of Pipeline Right-of Ways in the Appalachian Mountains. Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012178.
Pełny tekst źródłaTao, Yang, Victor Alchanatis, and Yud-Ren Chen. X-ray and stereo imaging method for sensitive detection of bone fragments and hazardous materials in de-boned poultry fillets. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7695872.bard.
Pełny tekst źródłaWorkman, Austin, and Jay Clausen. Meteorological property and temporal variable effect on spatial semivariance of infrared thermography of soil surfaces for detection of foreign objects. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41024.
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