Literatura académica sobre el tema "Neural border"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Neural border".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Neural border"
Li, Yongbin, Di Zhao, Takeo Horie, Geng Chen, Hongcun Bao, Siyu Chen, Weihong Liu et al. "Conserved gene regulatory module specifies lateral neural borders across bilaterians". Proceedings of the National Academy of Sciences 114, n.º 31 (17 de julio de 2017): E6352—E6360. http://dx.doi.org/10.1073/pnas.1704194114.
Texto completoZaaboub, Wala, Lotfi Tlig, Mounir Sayadi y Basel Solaiman. "Neural Network-based System for Automatic Passport Stamp Classification". Information Technology And Control 49, n.º 4 (19 de diciembre de 2020): 583–607. http://dx.doi.org/10.5755/j01.itc.49.4.25919.
Texto completoCraft, Edward, Hartmut Schütze, Ernst Niebur y Rüdiger von der Heydt. "A Neural Model of Figure–Ground Organization". Journal of Neurophysiology 97, n.º 6 (junio de 2007): 4310–26. http://dx.doi.org/10.1152/jn.00203.2007.
Texto completoMilet, Cécile y Anne H. Monsoro-Burq. "Neural crest induction at the neural plate border in vertebrates". Developmental Biology 366, n.º 1 (junio de 2012): 22–33. http://dx.doi.org/10.1016/j.ydbio.2012.01.013.
Texto completoShen, Jianjun. "Research on the International Trade Performance Evaluation of Cross-Border e-Commerce Based on the Deep Neural Network Model". Journal of Sensors 2022 (8 de octubre de 2022): 1–9. http://dx.doi.org/10.1155/2022/3006907.
Texto completoBirgbauer, E., J. Sechrist, M. Bronner-Fraser y S. Fraser. "Rhombomeric origin and rostrocaudal reassortment of neural crest cells revealed by intravital microscopy". Development 121, n.º 4 (1 de abril de 1995): 935–45. http://dx.doi.org/10.1242/dev.121.4.935.
Texto completoRideaux, Reuben y William J. Harrison. "Border ownership-dependent tilt aftereffect for shape defined by binocular disparity and motion parallax". Journal of Neurophysiology 121, n.º 5 (1 de mayo de 2019): 1917–23. http://dx.doi.org/10.1152/jn.00111.2019.
Texto completoLi, Yanting. "A Cloud Computing-Based Intelligent Forecasting Method for Cross-Border E-Commerce Logistics Costs". Advances in Mathematical Physics 2022 (29 de marzo de 2022): 1–10. http://dx.doi.org/10.1155/2022/3838293.
Texto completoLong, Gerald M. y Philip M. Garvey. "The Effects of Target Borders on Dynamic Visual Acuity: Practical and Theoretical Implications". Perception 17, n.º 6 (diciembre de 1988): 745–51. http://dx.doi.org/10.1068/p170745.
Texto completoZhao, ShuTong, Zhenjie Yin y Pingping Xie. "Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise". PeerJ Computer Science 10 (29 de febrero de 2024): e1911. http://dx.doi.org/10.7717/peerj-cs.1911.
Texto completoTesis sobre el tema "Neural border"
Blair, Joel. "Building a better Placode: Modeling Neural Plate Border interactions with hPSCs". University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663141272833.
Texto completoPatthey, Cédric. "Induction of the isthmic organizer and specification of the neural plate border". Doctoral thesis, Umeå universitet, Umeå centrum för molekylär medicin (UCMM), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1811.
Texto completoPatthey, Cédric. "Induction of the isthmic organizer and specification of the neural plate border /". Umeå : Univ, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1811.
Texto completoHerng, Eduardo Wu Jyh. "Detecção de bordas em imagens de ecocardiografia utilizando redes neurais artificiais". Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/98/98131/tde-04062012-083028/.
Texto completoBeing non-invasive and having low cost, the echocardiography has been largely applied as diagnostic technique for left ventricle systolic and diastolic volumes determination that indirectly are used to calculate the left ventricle ejection volume, the cardiac cavities muscular contraction, the regional and global ejection fraction, the myocardial thickness, the ventricular mass, etc. For this reason, the detection of the left ventricle endocardial borders become necessary, but hampered by the noise that impairs the echocardiography images definition. In spite of having many image segmentation techniques, this work intend to detect the borders of left ventricle on echocardiography images by using a artificial neural network to recognize border patterns. To accelerate the process and facilitate the procedure, the operator uses the mouse to define a rectangular region inside the acoustic window of the pacient where all analyses and border recognitions will be accomplished. After labeling the recognized points as \'border\', gradient techniques and mobile boundary are used to connect the points of greater probability and delineate the left ventricle border. This technique has proved to be efficient when compared to the borders traced by the specialist. The ability of the operator is important in choosing of the region to be analyzed. After training with 50 samples of \"border\" pattern and 10 samples of \"no-border\" pattern, this technique was tested on 108 images, achieving good results on precision and velocitiy when we compared the calculated left ventricle area with the results of other techniques published on national and international literature.
Rossi, Christy Cortez. "Early development of two cell populations at the neural plate border : rohon-beard sensory neurons and neural crest cells /". Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2008.
Buscar texto completoIncludes bibliographical references (leaves 112-120). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;
Liu, Boqi. "The gene regulatory network in the anterior neural plate border of ascidian embryos". Kyoto University, 2020. http://hdl.handle.net/2433/253119.
Texto completoWhite, Cory B. "A Neural Network Approach to Border Gateway Protocol Peer Failure Detection and Prediction". DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/215.
Texto completoGrieves, Roderick McKinlay. "The neural basis of a cognitive map". Thesis, University of Stirling, 2015. http://hdl.handle.net/1893/21878.
Texto completoAn, Min. "Positional cloning and functional analysis of the SF3B1gene in zebrafish". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180528932.
Texto completoGhimouz, Rym. "Caractérisation du rôle des facteurs de transcription Homez et CBFbeta au cours de la neurogenèse et de la formation de la crête neurale chez Xenopus laevis". Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209568.
Texto completoLe premier clone d’ADNc code pour l’homologue du facteur de transcription Homez, contenant trois homéodomaines et deux motifs leucine zipper et dont la fonction est inconnue. Mes résultats ont montré que chez l’embryon de xénope au stade neurula, Homez est exprimé préférentiellement dans la plaque neurale, l’expression la plus forte étant détectée dans les domaines où les neurones primaires apparaissent. Plus tard, Homez est détecté dans le tube neural dans des cellules neurales postmitotiques en cours de différenciation. En accord avec ce profil d’expression, j’ai observé que Homez est régulé positivement par l’atténuation des signaux BMPs et par le facteur proneural Ngnr1 et négativement par la voie Notch. Bien que le facteur Homez ne soit pas suffisant pour induire une expression ectopique de marqueurs neuronaux dans l’embryon de xénope, j’ai pu montrer, en utilisant une approche de morpholino antisens, que celui-ci est requis en aval du facteur Ngnr1 pour la différenciation des précurseurs neuraux en neurones primaires.
Le deuxième clone code pour l’homologue du facteur CBFβ qui s’associe avec une famille de protéines CBFα1-3/Aml1-3/Runx1-3 pour former un complexe hétérodimérique liant l’ADN. Alors que chez la souris, les facteurs Runx1 et Runx3 jouent un rôle important dans la neurogenèse dans les ganglions spinaux et que chez le xénope, Runx1 est requis pour la formation des neurones Rohon-Beard, le rôle de CBFβ au cours du développement du système nerveux est actuellement mal connu. Mes résultats ont montré que chez l’embryon de xénope au stade neurula, CBFβ est coexprimé avec les facteurs Runx1-3 en bordure de la plaque neurale, mais de manière plus étendue et plus précoce. Comme attendu pour un marqueur de la bordure de la plaque neurale, j’ai observé que l’expression de CBFβ est régulée par les signaux BMP, Wnt, FGF et Notch. De manière intéressante, son expression est induite par les facteurs proneuraux alors que celle de Runx1 est inhibée. Des expériences de perte de fonction à l’aide de morpholinos antisens bloquant la traduction de CBFβ ont été réalisées. Ces expériences suggèrent que le facteur CBFβ est nécessaire à la mise en place de la CN et à la différenciation des neurones de Rohon-Beard.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Libros sobre el tema "Neural border"
Chappell, Michael, Bradley MacIntosh y Thomas Okell. Introduction to Perfusion Quantification using Arterial Spin Labelling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198793816.001.0001.
Texto completoRijpma, Jorrit J. Brave New Borders: The EU’s Use of New Technologies for the Management of Migration and Asylum. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198807216.003.0007.
Texto completoAltman, Meryl. The Grand Rectification. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190608811.003.0008.
Texto completoAgius, Christine. Rescuing the State? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190644031.003.0005.
Texto completoKurevska, Līga. Designing Regulatory Framework for Demand Response Service Integration in Baltic Electricity Markets. RTU Press, 2022. http://dx.doi.org/10.7250/9789934227974.
Texto completoBindemann, Markus, ed. Forensic Face Matching. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198837749.001.0001.
Texto completoCapítulos de libros sobre el tema "Neural border"
Nakata, Yusuke y Ko Sakai. "Structures of Surround Modulation for the Border-Ownership Selectivity of V2 Cells". En Neural Information Processing, 383–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34475-6_46.
Texto completoZainal, Zaem Arif y Shunji Satoh. "Formulation of Border-Ownership Assignment in Area V2 as an Optimization Problem". En Neural Information Processing, 859–66. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70090-8_87.
Texto completoBronner-Fraser, Marianne. "The Neural Crest: Migrating from the Border". En Cell Migration in Development and Disease, 155–71. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527604669.ch9.
Texto completoSakai, Ko y Shunsuke Michii. "Latency Modulation of Border Ownership Selective Cells in V1-V2 Feed-Forward Model". En Neural Information Processing, 291–300. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42051-1_37.
Texto completoKikuchi, Masayuki y Youhei Akashi. "A Model of Border-Ownership Coding in Early Vision". En Artificial Neural Networks — ICANN 2001, 1069–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44668-0_148.
Texto completoHosoya, Haruo. "Bayesian Interpretation of Border-Ownership Signals in Early Visual Cortex". En Neural Information Processing. Theory and Algorithms, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17537-4_1.
Texto completoWagatsuma, Nobuhiko y Hirotoshi Konno. "The Effects of Feedback Signals Mediated by NMDA-Type Synapses for Modulating Border-Ownership Selective Neurons in Visual Cortex". En Neural Information Processing, 563–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04167-0_51.
Texto completoWagatsuma, Nobuhiko y Ko Sakai. "Roles of Early Vision for the Dynamics of Border-Ownership Selective Neurons". En Neural Information Processing. Theory and Algorithms, 99–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17537-4_13.
Texto completoRana, Mashud y Irena Koprinska. "Wavelet Neural Networks for Electricity Load Forecasting – Dealing with Border Distortion and Shift Invariance". En Artificial Neural Networks and Machine Learning – ICANN 2013, 571–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40728-4_71.
Texto completoJadhav, Ashwin R., Arun G. Ghontale y Vimal K. Shrivastava. "Segmentation and Border Detection of Melanoma Lesions Using Convolutional Neural Network and SVM". En Computational Intelligence: Theories, Applications and Future Directions - Volume I, 97–108. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1132-1_8.
Texto completoActas de conferencias sobre el tema "Neural border"
Carlos-Roca, Laura Rodriguez, Isabelle Hupont Torres y Carles Fernandez Tena. "Facial recognition application for border control". En 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 2018. http://dx.doi.org/10.1109/ijcnn.2018.8489113.
Texto completoKarimi, Mohsen, Ali Jahanshahi, Abbas Mazloumi y Hadi Zamani Sabzi. "Border Gateway Protocol Anomaly Detection Using Neural Network". En 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006201.
Texto completoHsu, Chih-Chieh y Alice C. Parker. "Border ownership in a nano-neuromorphic circuit using nonlinear dendritic computations". En 2014 International Joint Conference on Neural Networks (IJCNN). IEEE, 2014. http://dx.doi.org/10.1109/ijcnn.2014.6889690.
Texto completoQuan, Yu, Zhixin Li, Canlong Zhang y Huifang Ma. "Object Detection by Integrating Scene-Level Semantic Information and Border Regression Reinforcement". En 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206636.
Texto completoLiu, Tianying, Yang Wang, Siyun Hou, Wengen Li, Jihong Guan, Shuigeng Zhou y Rufu Qin. "RBA-CenterNet: Feature Enhancement by Rotated Border Alignment for Oriented Object Detection". En 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9534400.
Texto completoMishra, A., K. Sudan y H. Soliman. "Detecting border intrusion using wireless sensor network and artificial neural network". En 2010 International Conference on Distributed Computing in Sensor Systems Workshops (DCOSSW 2010). IEEE, 2010. http://dx.doi.org/10.1109/dcossw.2010.5593287.
Texto completoKrigel, Tina, RA Benjamin Schitze y Jonathan Stoklas. "Legal, ethical and social impact on the use of computational intelligence based systems for land border crossings". En 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 2018. http://dx.doi.org/10.1109/ijcnn.2018.8489349.
Texto completoPawlicki, Marek, Rafał Kozik y Michał Choraś. "Improving Siamese Neural Networks with Border Extraction Sampling for the use in Real-Time Network Intrusion Detection". En 2023 International Joint Conference on Neural Networks (IJCNN). IEEE, 2023. http://dx.doi.org/10.1109/ijcnn54540.2023.10191496.
Texto completoAli, Abder-Rahman, Jingpeng Li, Sally Jane O'Shea, Guang Yang, Thomas Trappenberg y Xujiong Ye. "A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images". En 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 2019. http://dx.doi.org/10.1109/ijcnn.2019.8852134.
Texto completoOkel, Sanne E., Fons van der Sommen, Endi Selmanaj, Joost A. van der Putten, Maarten R. Struyvenberg, Jacques J. Bergman y Peter H. N. de With. "Tissue-border detection in volumetric laser endomicroscopy using bi-directional gated recurrent neural networks". En Computer-Aided Diagnosis, editado por Karen Drukker y Maciej A. Mazurowski. SPIE, 2021. http://dx.doi.org/10.1117/12.2579751.
Texto completoInformes sobre el tema "Neural border"
Willson. L51756 State of the Art Intelligent Control for Large Engines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), septiembre de 1996. http://dx.doi.org/10.55274/r0010423.
Texto completoOlsen y Willson. L51916 Pressure Based Parametric Emission Monitoring Systems (PEMS). Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), abril de 2002. http://dx.doi.org/10.55274/r0010181.
Texto completoIrudayaraj, Joseph, Ze'ev Schmilovitch, Amos Mizrach, Giora Kritzman y Chitrita DebRoy. Rapid detection of food borne pathogens and non-pathogens in fresh produce using FT-IRS and raman spectroscopy. United States Department of Agriculture, octubre de 2004. http://dx.doi.org/10.32747/2004.7587221.bard.
Texto completoUK, Ipsos. Survey of public attitudes towards precision breeding. Food Standards Agency, octubre de 2022. http://dx.doi.org/10.46756/sci.fsa.ouv127.
Texto completo