Добірка наукової літератури з теми "Images radar marin"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Images radar marin".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Images radar marin"
Cai, Jun, George A. McMechan, and Michael A. Fisher. "Application of ground-penetrating radar to investigation of near-surface fault properties in the San Francisco Bay region." Bulletin of the Seismological Society of America 86, no. 5 (October 1, 1996): 1459–70. http://dx.doi.org/10.1785/bssa0860051459.
Повний текст джерелаChen, Duo, Ying Li, Yi Wen Wang, and Jin Xu. "Research on Marine Radar Image Collection Technology Based on OpenCV." Advanced Materials Research 798-799 (September 2013): 578–81. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.578.
Повний текст джерелаWang, Hui, Haiyang Qiu, Pengfei Zhi, Lei Wang, Wei Chen, Rizwan Akhtar, and Muhammad Asif Zahoor Raja. "Study of Algorithms for Wind Direction Retrieval from X-Band Marine Radar Images." Electronics 8, no. 7 (July 8, 2019): 764. http://dx.doi.org/10.3390/electronics8070764.
Повний текст джерелаMityagina, M. I. "Intensity of convective motions in marine atmospheric boundary layer retrieved from ocean surface radar imagery." Nonlinear Processes in Geophysics 13, no. 3 (July 24, 2006): 303–8. http://dx.doi.org/10.5194/npg-13-303-2006.
Повний текст джерелаMingozzi, Matteo, Francesca Salvioli, and Francesco Serafino. "X-Band Radar for Cetacean Detection (Focus on Tursiops truncatus) and Preliminary Analysis of Their Behavior." Remote Sensing 12, no. 3 (January 25, 2020): 388. http://dx.doi.org/10.3390/rs12030388.
Повний текст джерелаZhang, Chuang, Meihan Fang, Chunyu Yang, Renhai Yu, and Tieshan Li. "Perceptual Fusion of Electronic Chart and Marine Radar Image." Journal of Marine Science and Engineering 9, no. 11 (November 10, 2021): 1245. http://dx.doi.org/10.3390/jmse9111245.
Повний текст джерелаAustin, G. L., A. Bellon, M. Riley, and E. Ballantyne. "Navigation by Computer Processing of Marine Radar Images." Journal of Navigation 38, no. 3 (September 1985): 375–83. http://dx.doi.org/10.1017/s0373463300032744.
Повний текст джерелаChen, Zhongbiao, Yijun He, and Wankang Yang. "Study of Ocean Waves Measured by Collocated HH and VV Polarized X-Band Marine Radars." International Journal of Antennas and Propagation 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/8257930.
Повний текст джерелаWei, Yanbo, Yalin Liu, Yifei Lei, Ruiyao Lian, Zhizhong Lu, and Lei Sun. "A New Method of Rainfall Detection from the Collected X-Band Marine Radar Images." Remote Sensing 14, no. 15 (July 27, 2022): 3600. http://dx.doi.org/10.3390/rs14153600.
Повний текст джерелаJi, Xing, Jia Yuan Zhuang, and Yu Min Su. "Marine Radar Target Detection for USV." Advanced Materials Research 1006-1007 (August 2014): 863–69. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.863.
Повний текст джерелаДисертації з теми "Images radar marin"
Michelet, Jordan. "Extraction du fouillis de mer dans des images radar marin cohérent : modèles de champ de phases, méthodes de Boltzmann sur réseau, apprentissage." Electronic Thesis or Diss., La Rochelle, 2022. http://www.theses.fr/2022LAROS048.
Повний текст джерелаWe focus on the problem of sea clutter extraction in marine radar images. The aim is to develop image processing methods allowing us to avoid assumptions about the nature of the sea clutter and the signal of interest. On the one hand, we propose an original algorithm based on a variational approach : a multiphase model with diffuse interface. The results obtained show that the algorithm is efficient when the signal of interest has a sufficiently large signal-to-clutter ratio. On the other hand, we focus on the implementation of lattice Boltzmann schemes for convection-diffusion problems with non-constant advection velocity and non-zero source term. We describe the computation of the consistency obtained by asymptotic analysis at the acoustic scale and with a multiple relaxation time collision operator, and study the stability of these schemes in a particular case. The obtained results show that the proposed schemes allow removing the residual noise and to enhance the signal of interest on the image obtained with the first method. Finally, we propose a learning method allowing us to avoid assumptions on the nature of the signal of interest. Indeed, in addition to the variational approach, we propose an algorithm based on pulse-Doppler processing when the signal of interest is exo-clutter and has a low signal-to-clutter ratio. The results obtained from the proposed double auto-encoder, being comparable to the results provided by each of the two methods, allow validating this approach
Jolly, Alistair Duncan. "Feature extraction from millimetre wave radar images." Thesis, University of Central Lancashire, 1992. http://clok.uclan.ac.uk/19034/.
Повний текст джерелаQi, Yusheng Ph D. Massachusetts Institute of Technology. "Sea surface wave reconstruction from marine radar images." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/74939.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (p. 103-105).
The X-band marine radar is one type of remote sensing technology which is being increasingly used to measure sea surface waves nowadays. In this thesis, how to reconstruct sea surface wave elevation maps from X-band marine radar images and do wave field prediction over short term in real time are discussed. The key idea of reconstruction is using dispersion relation based on the linear wave theory to separate the wave-related signal from non-wave signal in radar images. The reconstruction process involves three-dimensional Fourier analysis and some radar imaging mechanism. In this thesis, an improved shadowing simulation model combined with wave field simulation models for the study of the correction function in the reconstruction process and an improved wave scale estimation model using non-coherent radar data are proposed, which are of great importance in the reconstruction process. A radar image calibration method based on wave field simulation is put forward in order to improve the quality of reconstructed sea surface wave. Besides, a theoretical wave scale estimation model using Doppler spectra of the coherent radar is put forward, which is proposed to be a good alternative to the current wave scale estimation model. The reconstructed sea surface wave can be used for wave field simulation in order to predict the wave field, which is not only an application of this reconstruction process, but also a parameter optimizing tool for the reconstruction process.
by Yusheng Qi.
S.M.
Svensson, Henrik. "Simultaneous Localization And Mapping in a Marine Environment using Radar Images." Thesis, Linköping University, Automatic Control, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-20845.
Повний текст джерелаSimultaneous Localization And Mapping (SLAM) is a process of mapping an unknown environment and at the same time keeping track of the position within this map. In this theses, SLAM is performed in a marine environent using radar images only.
A SLAM solution is presented. It uses SIFT to compare pairs of radar images. From these comparisons, measurements of the boat movements are obtained. A type of Kalman filter (Exactly Sparse Delayed-state Filter, ESDF) uses these measurements to estimate the trajectory of the boat. Once the trajectory is estimated, the radar images are joined together in order to create a map.
The presented solution is tested and the estimated trajectory is compared to GPS data. Results show that the method performs well for at least shorter periods of time.
Trebossen, Hervé. "Apport des images RADAR à synthèse d'ouverture à la cartographie marine." Marne-la-Vallée, 2002. http://www.theses.fr/2002MARN0140.
Повний текст джерелаMore half of the carriage of goods throughout the world is done by sea. One of the means allowing to ensure the safety of the ships and consequently to avoid accidental pollution, is to put at provision of the sailors of the sea charts of quality, in conformity with the modern means of navigation (navigation by GPS). Unfortunately, currently, these documents of navigation are old on a number of coastal zones. The SHOM who is in charge in France of the establishment and of the diffusion of nautical information, uses, in certain cases, to bring up to date its cards more quickly, of the images of remote sensing coming from the optical satellites SPOT. In zones with strong nebulosity, the acquisition of such data is very random, the images of the satellites with Synthetic Aperture RADAR (SAR) bring the advantage of not being disturbed by the cloud cover. Present study is borned of collaboration between SHOM and UMLV, its main goal is to develop a method to use SAR images in order to facilitate nautical chart reactualisation. First chapter of this work presents, on each various site which "will be auscultated" through images radar with synthesis of opening, great characteristics of the medium, the data base images and cards then interest of the site for marine cartography. The five coastal sites presented are partly in humid tropical area (French Guiana, Cameroon, Gabon), in polar zone (Terre-Adélie) and last in arid inter-tropical area (Mauritania). Second chapter relates to the radiometric and geometrical processing implemented for the use of the images radar. Radiometric processing will comprise mainly the use of known algorithms for filtering of the speckle on amplitude images, generating coherence images with complex SAR data and extracting automatically information from SAR data. With regard to the geometrical processing, we chose to develop a tool in order to georeference our ERS images database. This tool requires to know satellite orbitography, geoid height on study site and internal satellite geometry. Validation of this tool will be based on ground control points acquisition and on comparison between ERS images acquired in ascending and descending pass. SAR data analysis will be done on topics interesting nautical charts updating: shallow waters close to coast, on inter-tidal zone, and finally, on terrestrial part, coastal vegetation and anthropic zones. Other remote sensing data (optical and different SAR data) could be used, according to availabilities, to enrich our matter. Last, fourth chapter is devoted with re-actualisations of nautical charts in which we participated. We propose new cartographic products including recent SAR images and older data from nautical charts, to compensate lack of traditional maps up to date and likely to integrated evolutions observed study sites
Wang, Yuanxun. "Radar signature prediction and feature extraction using advanced signal processing techniques /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
Повний текст джерелаAljohani, Mansour Abdullah M. "A Technique for Magnetron Oscillator Based Inverse Synthetic Aperture Radar Image Formation." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1571665145862203.
Повний текст джерелаAssali, Camille. "Contribution des radars embarqués à l'étude des stratégies collectives de recherche alimentaire chez les oiseaux marins." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT075/document.
Повний текст джерелаIn the ocean, prey is patchily distributed. To overcome this challenge, pelagic seabirds benefit from social information from conspecifics, heterospecifics, or fishing boats.As part of this dissertation, we aim at evaluating the influence of different information sources in seabird foraging strategies in the tropical pelagic environment.Seabirds can detect visible predators or boats at distances of over ten kilometres. We thus study the distribution of seabirds at sub-meso-scale, analysing images recorded from a radar on board a tuna purse-seiner. Radar images provide a visualisation of the instantaneous distribution of the in-flight seabird community as well as seabird movements within thirty kilometres of the seiner. We detect over-aggregatedand temporary patterns, spanning about ten kilometers, within flying seabirds’ distribution. Distancesbetween seabird groups are compatible with information exchanges within these aggregations. A finer scale study reveals coordinated flights of seabird groups distant of hundreds of meters from each others (« rakes »), and suggesting a high level of coordination during foraging. We then investigate the potential disturbance induced by the seiner in the seabirds’ foraging network.First results indicate that seabirds can discriminate the different seiner’s activities.To our knowledge, this work is the first contribution of on board radars use for the study of seabird ecology in the high seas, and opens interesting perspectives, such as the understanding of interactions’ dynamics within the marine top-predators guild
Margarit, Martín Gerard. "Marine applications of SAR polarimetry." Doctoral thesis, Universitat Politècnica de Catalunya, 2007. http://hdl.handle.net/10803/6944.
Повний текст джерелаFins l'actualitat, diferents propostes s'han estudiat per monitorar vaixells, com per exemple transpondedors, teledetecció òptica i sensors acústics passius. L'experiència en entorns reals ha demostrat que cap d'aquestes solucions és eficient. Una alternativa poden ser els Radars d'Obertura Sintètica (SAR). Aquests sistemes utilitzen les propietats de reflectivitat i dispersió dels vaixells per identificar-los amb independència de qualsevol fenomen atmosfèric i del cicle dia/nit. El sensors SAR sintetitzen una obertura més gran que la real permetent l'obtenció d'imatges de reflectivitat d'uns quants kilòmetres d'amplada amb una resolució de pocs metres.
En la monitorització de vaixells, la tecnologia SAR ha demostrat unes bones prestacions per la detecció. Treu profit del fet que els vaixells dispersen més energia que el mar i, així, apareixen en les imatges com punts molt brillants. Però, la seva utilitat en la identificació de vaixells encara no està clara. Hi ha dues limitacions importants: 1) les resolucions dels sistemes actuals no semblen suficients per aïllar característiques geomètriques a partir de la informació de reflectivitat i 2) les distorsions que les signatures dels vaixells experimenten en entorns marins. Aquests problemes es poden resoldre parcialment si s'utilitzen dades SAR multidimensional. Aquest concepte es refereix al fet d'adquirir imatges SAR modificant un o més paràmetres del sistema. En la classificació de vaixells, hi ha dues opcions clares: 1) Polarimetria SAR (PolSAR) que utilitza les dues components polarimètriques de l'ona EM i 2) la Interferometria SAR que s'obté per la combinació de dues imatges SAR adquirides des de posicions molt properes. Per a una banda, la polarització de l'ona EM és una propietat intrínseca de l'ona que ajuda a aïllar estructures geomètriques particulars per mitjà de la teoria de descomposició de blancs (TD). Per l'altra, la interferometria treu profit de la diferencia de fase entre les dues imatges SAR per obtenir la tercera dimensió de l'escena.
PolSAR and InSAR presenten grans possibilitats per la monitorització de vaixells ja que poden solucionar algunes de les limitacions dels mètodes clàssics. Desafortunadament, encara no han estat profundament estudiades a causa de les dificultats en obtenir dades reals validades. Això ha limitat el nombre d'estudis en aquesta temàtica. En aquest entorn, la tesi està orientada a avaluar fins a quin punt les tècniques PolSAR i InSAR poden ser útils per la monitorització de vaixells. Per a tal propòsit, s'han fixat quatre objectius importants:
1. El desenvolupament d'un simulador SAR eficient que doni imatges realistes de vaixells i que solucioni el dèficit de dades reals en entorns marins.
2. L'estudi de la dispersió dels vaixells que fixi els principals mecanismes de dispersió observats en imatges SAR i com es relacionen amb la geometria dels vaixells.
3. Un estudi de les prestacions de les tècniques actuals d'anàlisis de dades PolSAR en la classificació de vaixells.
4. El desenvolupament d'un mètode nou i eficient per la identificació de vaixells.
Al llarg de la tesis, els diferents punts seran estudiats i resolts. El desenvolupament de GRECOSAR, un simulador SAR de blancs complexes que dóna imatges de vaixells similars a les adquirides en entorns reals, ha estat essencial per estudiar les propietats de dispersió dels vaixells. Ha permès demostrar que els vaixells es poden distingir a partir del seu patró dispersiu, el qual és senzill i dominat per alguns dispersors guia que presenten una marcada estabilitat i potència de dispersió. Amb aquests resultats ha estat possible desenvolupar un nou mètode que pot identificar vaixells sota condicions d'observació adverses. Combina característiques polarimètriques i interferomètriques SAR (PolInSAR) per inferir estimacions 3D de la geometria dels vaixells. Diferents tests han demostrat que aquest mètode dóna una millor fiabilitat en la identificació que altres mètodes actualment disponibles. Malgrat tot, fixa uns requeriments tecnològics més elevats, sobretot en la resolució de les imatges i en les característiques PolInSAR. La nova generació de sensors SAR els poden cobrir.
Oceans support a complex and fragile chain that links a high number of biological, sociological and economical factors. In these days, this ecosystem is endangered by human activity and one of the main hot spots is overfishing. As a result, authorities worldwide have become aware about the necessity to law-protect the marine environment in order to assure the safety and sustenance of human beings. This demands the development of fisheries policy to monitor the activities of ships.
Up to now, different vessel monitoring proposals have been considered, for instance transponders, optical remote sensing or passive acoustic sensors. The lessons learnt in real scenarios have shown that none of these solutions is efficient. A feasible option may be the so-called active Synthetic Aperture Radar (SAR) technology. It uses the reflectivity/scattering properties of vessels for basing the identification process with independence of any atmospheric phenomena and day/night cycle. SAR sensors synthesize an antenna aperture larger than the real one and this allows to acquire reflectivity images of some tens of kilometers wide with a resolution of few meters.
In vessel monitoring, SAR imagery has proven good performance for vessel detection. They take profit of the fact that vessels normally backscatter more power than the sea and, hence, they appear in the images as bright spots. But their usefulness in vessel identification has not been established yet. There are two main limitations, namely: 1) the resolution of current systems that appears to be not enough for isolating geometrical features from the reflectivity information of SAR images and 2) the distortions that vessel' signatures experiment within sea scenarios. Such problems can be solved up to certain extend if multidimensional SAR data is used. This concept refers to the possibility to acquire different SAR images by modifying one or more imaging parameters. In the scope of vessel classification, there are two main options, namely: 1) SAR polarimetry (PolSAR) that refers to the usage of the two polarimetric components of the EM wave and 2) SAR interferometry (InSAR) derived by combining two SAR images acquired from slightly different positions. On the one hand, the polarization of an EM wave is an intrinsic wave property that helps on identifying specific geometrical structures via Target Decomposition (TD) theory. On the other hand, Interferometry takes profit of the phase difference between the two SAR images to retrieve the third dimension of the scene.
PolSAR and InSAR have great potentialities for supporting vessel monitoring as they can overcome some of the limitations of classical methods. Unfortunately, they have not been exploited yet due to the difficulties on having at one's disposal real data with reliable ground-truth. This has limited the number of works tackling such issue. In this framework, the current thesis is focused to evaluate up to which extend PolSAR and InSAR imagery are reliable for vessel monitoring. For such purpose, four main goals are proposed, namely:
1. The development of an efficient SAR simulation environment that provides realistic vessel SAR images and overcomes the current data deficiency related to marine scenarios.
2. The study of vessel scattering to fix the main polarimetric scattering mechanisms observed in vessel SAR images and how they are related with the geometries of vessels.
3. A performance study of current analysis tools of PolSAR data in vessel classification.
4. The development of a novel and efficient methodology for vessel identification.
Along the thesis, the different points are studied and solved. The development of GRECOSAR, a SAR simulator of complex targets able to provide vessel images similar to those obtained in real scenarios, has been essential for studying the scattering properties of vessels. It has allowed to show that vessels can be distinguished by means of their scattering pattern, which appear to be not so complex and dominated by some guide scatters that present a marked reflectivity stability and scattered power. With these results, a new approach able to identify vessels even under adverse observation conditions has been developed. It combines polarimetric and interferometric SAR (PolInSAR) capabilities to retrieve 3D estimates of the geometry of ships. Different tests have shown that the proposed method provides better identification confidence than other available methods. However, it demands higher technological requirements in terms of image resolution and PolInSAR features. The new generation of SAR sensors may fulfill them.
Martinez, Garcia Javier [Verfasser], Martin [Akademischer Betreuer] Vossiek, Christian [Gutachter] Waldschmidt, and Mario [Gutachter] Huemer. "Classification of MIMO-FMCW radar images with convolutional neural networks in a parking monitoring application / Javier Martinez Garcia ; Gutachter: Christian Waldschmidt, Mario Huemer ; Betreuer: Martin Vossiek." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2020. http://d-nb.info/1214443494/34.
Повний текст джерелаКниги з теми "Images radar marin"
Automatic Detection Algorithms of Oil Spill in Radar Images. Taylor & Francis Group, 2019.
Знайти повний текст джерелаMarghany, Maged. Automatic Detection Algorithms of Oil Spill in Radar Images. Taylor & Francis Group, 2019.
Знайти повний текст джерелаMarghany, Maged. Automatic Detection Algorithms of Oil Spill in Radar Images. Taylor & Francis Group, 2021.
Знайти повний текст джерелаMarghany, Maged. Automatic Detection Algorithms of Oil Spill in Radar Images. Taylor & Francis Group, 2019.
Знайти повний текст джерелаЧастини книг з теми "Images radar marin"
Picetti, Francesco. "How Deep Learning Can Help Solving Geophysical Inverse Problems." In Special Topics in Information Technology, 141–52. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15374-7_12.
Повний текст джерелаZhang, Jiaju, Zhen Zuo, Sun Bei, Peng Wu, and Honghe Huang. "UKF-EC: Combining the Unscented Kalman Filter and the Maximum Weight Algorithms for Moving Target Tracking in Marine Radar Images." In Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022), 1830–44. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0479-2_170.
Повний текст джерелаChen, Xinwei, Weimin Huang, and Björn Lund. "Wind parameter measurement using X-band marine radar images." In Ocean Remote Sensing Technologies: High frequency, marine and GNSS-based radar, 401–24. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/sbra537e_ch17.
Повний текст джерелаYahia, Mohamed, and Tarig Ali. "SAR Image Denoising using MMSE Techniques." In Denoising - New Insights [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.108362.
Повний текст джерелаChernyshov, Pavel, Teodor Vrecica, and Yaron Toledo. "Wavelet-based methods to invert sea surfaces and bathymetries from X-band radar images." In Ocean Remote Sensing Technologies: High frequency, marine and GNSS-based radar, 313–31. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/sbra537e_ch13.
Повний текст джерелаVijayakumar, Singanamalla. "Computational Techniques of Oil Spill Detection in Synthetic Aperture Radar Data: Review Cases." In Recent Oil Spill Challenges That Require More Attention [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.108115.
Повний текст джерелаHabeeb Alghanimi, Abdulhameed. "Medical Application of Ultra-Wideband Technology." In Innovations in Ultra-Wideband Technologies. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93577.
Повний текст джерела"A Targets Detection Approach Based on an improved R-CNN Algorithm for Inland River Crossing Area Marine Radar Image." In Proceedings of the International Seminar on Safety and Security of Autonomous Vessels (ISSAV) and European STAMP Workshop and Conference (ESWC) 2019, 58–72. Sciendo, 2020. http://dx.doi.org/10.2478/9788395669606-006.
Повний текст джерелаMostipan, Oleksandr. "PERSPECTIVES OF MODERNIZATION OF THE COMMUNICATION STRATEGY OF THE VERKHOVNA RADA OF UKRAINE FOR 2017-2021 YEARS." In Integration of traditional and innovation processes of development of modern science. Publishing House “Baltija Publishing”, 2020. http://dx.doi.org/10.30525/978-9934-26-021-6-9.
Повний текст джерелаТези доповідей конференцій з теми "Images radar marin"
O'Connell, Barbara J. "Ice Hazard Radar." In SNAME 9th International Conference and Exhibition on Performance of Ships and Structures in Ice. SNAME, 2010. http://dx.doi.org/10.5957/icetech-2010-179.
Повний текст джерелаO’Connell, Barbara J. "Marine Radar for Improved Ice Detection." In SNAME 8th International Conference and Exhibition on Performance of Ships and Structures in Ice. SNAME, 2008. http://dx.doi.org/10.5957/icetech-2008-136.
Повний текст джерелаLi, Wei, Houxiang Zhang, and Ottar L. Osen. "A UAV SAR Prototype for Marine and Arctic Application." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61264.
Повний текст джерелаWijaya, A. P. "Towards Nonlinear Wave Reconstruction and Prediction From Synthetic Radar Images." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54496.
Повний текст джерелаChen, Xiaolong, Jian Guan, Zhigao Wang, Hai Zhang, and Guoqing Wang. "Marine Targets Detection for Scanning Radar Images Based on Radar- YOLONet." In 2021 CIE International Conference on Radar (Radar). IEEE, 2021. http://dx.doi.org/10.1109/radar53847.2021.10028264.
Повний текст джерелаChen, Xinwei, and Weimin Huang. "Rain Detection From X-Band Marine Radar Images." In 2019 IEEE Radar Conference (RadarConf19). IEEE, 2019. http://dx.doi.org/10.1109/radar.2019.8835559.
Повний текст джерелаFrejlichowski, Dariusz, and Andrzej Lisaj. "Analysis of lossless radar images compression for navigation in marine traffic and remote transmission." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4720964.
Повний текст джерелаNieto-Borge, Jose C., Victor del Estal-Fernandez, Pilar Jarabo-Amores, and Konstanze Reichert. "Moving ship detection in presence of sea clutter from temporal sequences of marine radar images." In 2008 International Conference on Radar (Radar 2008). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4653897.
Повний текст джерелаNieto-Borge, Jose C., Ana M. Baquero-Martinez, David de la Mata-Moya, and Jose L. Alvarez-Perez. "Analysis of the sea clutter structure using temporal sequences of X-band marine radar images." In 2008 International Conference on Radar (Radar 2008). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4653987.
Повний текст джерелаNieto-Borge, Jose C., Katrin Hessner, Pilar Jarabo-Amores, and David de la Mata Moya. "Analysis of sea state parameters and ocean currents from temporal sequences of marine radar images of the sea surface." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4721062.
Повний текст джерелаЗвіти організацій з теми "Images radar marin"
Werle, D. Radar remote sensing for application in forestry: a literature review for investigators and potential users of SAR data in Canada. Natural Resources Canada/CMSS/Information Management, 1989. http://dx.doi.org/10.4095/329188.
Повний текст джерелаDeschamps, Robert, and Henschel. PR-420-133721-R01 Comparison of Radar Satellite Methods for Observation of Stability. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 2015. http://dx.doi.org/10.55274/r0010840.
Повний текст джерела