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Dissertations / Theses on the topic '3D Neuron Reconstruction'

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1

Mayerich, David Matthew. "Acquisition and reconstruction of brain tissue using knife-edge scanning microscopy." Texas A&M University, 2003. http://hdl.handle.net/1969.1/563.

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A fast method for gathering large-scale data sets through the serial sectioning of brain tissue is described. These data sets are retrieved using knife-edge scanning microscopy, a new technique developed in the Brain Networks Laboratory at Texas A&M University. This technique allows the imaging of tissue as it is cut by an ultramicrotome. In this thesis the development of a knife-edge scanner is discussed as well as the scanning techniques used to retrieve high-resolution data sets. Problems in knife-edge scanning microscopy, such as illumination, knife chatter, and focusing are discussed. Tec
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Koo, Stephanie C. "3D reconstruction of synaptic and nuclear corticosteroid receptors distribution density in the amygdala: a feasibility study." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/103629/1/Stephanie_Koo_Thesis.pdf.

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This project tested a new way of looking at different types of stress receptors (corticosteroid receptors) in the brain. The method used fluorescent markers to label the stress receptors in brain tissue, and reconstructed microscope images in 3D by using computer software. The thesis details this new method, and demonstrates how it can be used to compare different types of stress receptors, at different locations in the amygdala.
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Maack, Nina. "3D Reconstruction of Neural Circuits from Serial EM Images." Diss., lmu, 2008. http://nbn-resolving.de/urn:nbn:de:bvb:19-86627.

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4

Grundberg, Måns, and Viktor Altintas. "Generating 3D Scenes From Single RGB Images in Real-Time Using Neural Networks." Thesis, Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43091.

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The ability to reconstruct 3D scenes of environments is of great interest in a number of fields such as autonomous driving, surveillance, and virtual reality. However, traditional methods often rely on multiple cameras or sensor-based depth measurements to accurately reconstruct 3D scenes. In this thesis we propose an alternative, deep learning-based approach to 3D scene reconstruction for objects of interest, using nothing but single RGB images. We evaluate our approach using the Deep Object Pose Estimation (DOPE) neural network for object detection and pose estimation, and the NVIDIA Deep le
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Papadopoulos, Georgios. "Towards a 3D building reconstruction using spatial multisource data and computational intelligence techniques." Thesis, Limoges, 2019. http://www.theses.fr/2019LIMO0084/document.

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La reconstruction de bâtiments à partir de photographies aériennes et d’autres données spatiales urbaines multi-sources est une tâche qui utilise une multitude de méthodes automatisées et semi-automatisées allant des processus ponctuels au traitement classique des images et au balayage laser. Dans cette thèse, un système de relaxation itératif est développé sur la base de l'examen du contexte local de chaque bord en fonction de multiples sources d'entrée spatiales (masques optiques, d'élévation, d'ombre et de feuillage ainsi que d'autres données prétraitées, décrites au chapitre 6). Toutes ces
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6

Westerhoff, Malte. "Efficient visualization and reconstruction of 3D geometric models from neuro-biological confocal microscope scans." [S.l. : s.n.], 2001. http://www.diss.fu-berlin.de/2004/19/index.html.

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7

Liu, Ruixu. "Attention Based Temporal Convolutional Neural Network for Real-time 3D Human Pose Reconstruction." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton157546836015948.

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8

Bartoli, Simone. "Deploying deep learning for 3D reconstruction from monocular video sequences." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22402/.

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3D reconstruction from monocular video sequences is a field of increasingly interest in the late years. Before the growth of deep learning, the retrieve of depth information from single images was possible only with RGBD sensors or algorithmic approaches. However, the availability of more and more data has allowed the training of monocular depth estimation neural networks, introducing innovative data-driven techniques. Since recovering ground-truth labels for depth estimation is very challenging, most of the research has focused on unsupervised or semi-supervised training approaches. The curre
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Hanslovsky, Philipp [Verfasser], and Fred [Akademischer Betreuer] Hamprecht. "Isotropic Reconstruction of Neural Morphology from Large Non-Isotropic 3D Electron Microscopy / Philipp Hanslovsky ; Betreuer: Fred Hamprecht." Heidelberg : Universitätsbibliothek Heidelberg, 2019. http://d-nb.info/1200021622/34.

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10

Dai, Peilun. "Towards optical connectomics : feasibility of 3D reconstruction of neural morphology using expansion microscopy and in situ molecular barcoding." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120630.

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Thesis: S.M. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 27-29).<br>Reconstruction of the 3D morphology of neurons is an essential step towards the analysis and understanding of the structures and functions of neural circuits. Optical microscopy has been a key technology for mapping brain circuits throughout the history of neuroscience due to its low cost, wide usage in biological sciences and ability to read out information-rich molecular signals
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11

Lai, Po Kong. "Immersive Dynamic Scenes for Virtual Reality from a Single RGB-D Camera." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39663.

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In this thesis we explore the concepts and components which can be used as individual building blocks for producing immersive virtual reality (VR) content from a single RGB-D sensor. We identify the properties of immersive VR videos and propose a system composed of a foreground/background separator, a dynamic scene re-constructor and a shape completer. We initially explore the foreground/background separator component in the context of video summarization. More specifically, we examined how to extract trajectories of moving objects from video sequences captured with a static camera. We the
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12

Matteo, Lionel. "De l’image optique "multi-stéréo" à la topographie très haute résolution et la cartographie automatique des failles par apprentissage profond." Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4099.

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Les failles sismogéniques sont la source des séismes. L'étude de leurs propriétés nous informe donc sur les caractéristiques des forts séismes qu'elles peuvent produire. Les failles sont des objets 3D qui forment des réseaux complexes incluant une faille principale et une multitude de failles et fractures secondaires qui "découpent" la roche environnante à la faille principale. Mon objectif dans cette thèse a été de développer des approches pour aider à étudier cette fracturation secondaire intense. Pour identifier, cartographier et mesurer les fractures et les failles dans ces réseaux, j'ai a
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13

Detton, Alan James. "The Creation of a 3D Interactive Human Neural Development Resource and Its Evaluation Through a Video Analytic Usability Study." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337966847.

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14

Brishoual, Morgan. "Reconstruction de données : Application à la dosimétrie des radiotéléphones." Phd thesis, INSA de Rennes, 2001. http://tel.archives-ouvertes.fr/tel-00001750.

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Dans le cadre de la vérification de la conformité aux normes des personnes exposées aux champs électromagnétiques des radiotéléphones, une méthodologie a été développée permettant d'évaluer les champs électriques qui ne sont pas accessibles par la mesure. <br /><br />Des études ont montré qu'une large partie de la puissance absorbée est concentrée dans les tissus proches de l'antenne du radiotéléphone. Ces tissus englobant la région de l'oreille sont les plus exposés aux champs électromagnétiques. A l'interface peau - mobile, les valeurs de champs électriques sont donc importantes et décroisse
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15

Li, Vladimir. "Evaluation of the CNN Based Architectures on the Problem of Wide Baseline Stereo Matching." Thesis, KTH, Datorseende och robotik, CVAP, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-192476.

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Three-dimensional information is often used in robotics and 3D-mapping. There exist several ways to obtain a three-dimensional map. However, the time of flight used in the laser scanners or the structured light utilized by Kinect-like sensors sometimes are not sufficient. In this thesis, we investigate two CNN based stereo matching methods for obtaining 3D-information from a grayscaled pair of rectified images.While the state-of-the-art stereo matching method utilize a Siamese architecture, in this project a two-channel and a two stream network are trained in an attempt to outperform the state
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16

Orts-Escolano, Sergio. "A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs." Doctoral thesis, Universidad de Alicante, 2013. http://hdl.handle.net/10045/36484.

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The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-O
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17

Bolognini, Damiano. "Improving the convergence speed of NeRFs with depth supervision and weight initialization." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25656/.

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Neural rendering is a new and developing field where computer graphics and deep learning techniques are combined to generate photo-realistic images using deep neural networks. In particular, Neural Radiance Fields (NeRF) is able to synthesise novel views of a scene with unprecedented quality by fitting a Multi-Layer Perceptron (MLP) to RGB images. However, training this network requires plenty of time and computation even on modern GPUs, making this new technology hardly employable on practical specialized applications. In this project, we show that employing the known depth of the scen
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18

Ekström, Marcus. "Road Surface Preview Estimation Using a Monocular Camera." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151873.

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Recently, sensors such as radars and cameras have been widely used in automotives, especially in Advanced Driver-Assistance Systems (ADAS), to collect information about the vehicle's surroundings. Stereo cameras are very popular as they could be used passively to construct a 3D representation of the scene in front of the car. This allowed the development of several ADAS algorithms that need 3D information to perform their tasks. One interesting application is Road Surface Preview (RSP) where the task is to estimate the road height along the future path of the vehicle. An active suspension cont
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19

Kumar, Kanuj. "Reconstruction of 3D Neuronal Structures." Thesis, 2013. http://hdl.handle.net/2005/3280.

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Microscopic analysis of biological structures can be significantly enhanced by representing the object of study as a three-dimensional entity. To assist neurobiologists investigate the molecular mechanisms involved in neurite formation requires an adequate visual model or at least some measurable data. Reconstruction helps analysis of biological structures by representing the object of study as a three-dimensional entity. It helps gain insight into the morphological variation observed in each class of neurons and for simulations of neuronal behavior. To perform the reconstruction, biologists t
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20

Liu, Kendra, Sarah MacNamee, Stephen Gerhard, et al. "Morphological examination of the relationship between astrocyte-like glia and neuronal synapses in Drosophila." 2016. http://hdl.handle.net/10150/603647.

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Poster exhibited at GPSC Student Showcase, February 24th, 2016, University of Arizona. Recipient of the 2016 Katheryne B. Willock Library Research Award.<br>The nervous system is composed of two types of cells: neurons and glia. In neuronal circuits, neurons communicate through synapses and glia play a crucial modulatory role. To modulate chemical reuptake, glia send processes close to synapses and many glia directly appose or ensheathe a synapse. This structural motif is one of the elements often included in describing a vertebrate tripartite synapse, which includes a bidirectional functional
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21

TASI, BO-WEN, and 蔡博文. "3D Scene Reconstruction from YouTube Car Accident Videos Using Deep Neural Networks." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/wr4q59.

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碩士<br>國立臺灣科技大學<br>電子工程系<br>107<br>With the development of self-driving cars, the car accident detection and prevention based on deep learning technologies have received attention in recent years. To this end, collecting and analyzing car accident datasets becomes a critical issue. and the car accident videos from YouTube provide valuable resource. Hence, the objective of this research is to develop a tool for automatically reconstruction the 3D scenes from massive car accident videos. Specifically, we attempt to estimate the depth information of moving vehicles for the front-view images. Howev
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22

Maack, Nina [Verfasser]. "3D reconstruction of neural circuits from serial EM images / vorgelegt von Nina Maack." 2008. http://d-nb.info/989525732/34.

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23

Westerhoff, Malte [Verfasser]. "Efficient visualization and reconstruction of 3D geometric models from neuro-biological confocal microscope scans / vorgelegt von Malte Westerhoff." 2001. http://d-nb.info/970063016/34.

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24

Bhat, Shariq. "Depth Estimation Using Adaptive Bins via Global Attention at High Resolution." Thesis, 2021. http://hdl.handle.net/10754/668894.

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We address the problem of estimating a high quality dense depth map from a single RGB input image. We start out with a baseline encoder-decoder convolutional neural network architecture and pose the question of how the global processing of information can help improve overall depth estimation. To this end, we propose a transformer-based architecture block that divides the depth range into bins whose center value is estimated adaptively per image. The nal depth values are estimated as linear combinations of the bin centers. We call our new building block AdaBins. Our results show a deci
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Hsieh, Chia-Wen, and 謝佳彣. "Using Artificial Neural Network for Automatic Detection and Classification of Pulmonary Nodules in Lung CT and 3D Reconstruction and Volume Measurement." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/ua66es.

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碩士<br>國立臺灣科技大學<br>材料科學與工程系<br>107<br>Lung cancer has the highest mortality among all cancers, and if the pulmonary nodules and categories can be detected correctly and early, then the treatment effect on the patient can be enhanced. Clinically, the pulmonary nodules are screened according to the doctor's diagnosis, whereby they are searched for and their severity is evaluated according to size and appearance. As pulmonary nodules have different sizes and forms, they are sometimes unlikely to be detected in the image during early diagnosis. Therefore, this study develops a computer-aided diagno
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Gouiaa, Rafik. "Reconnaissance de postures humaines par fusion de la silhouette et de l'ombre dans l'infrarouge." Thèse, 2017. http://hdl.handle.net/1866/19538.

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Les systèmes multicaméras utilisés pour la vidéosurveillance sont complexes, lourds et coûteux. Pour la surveillance d'une pièce, serait-il possible de les remplacer par un système beaucoup plus simple utilisant une seule caméra et une ou plusieurs sources lumineuses en misant sur les ombres projetées pour obtenir de l'information 3D ? Malgré les résultats intéressants offerts par les systèmes multicaméras, la quantité d'information à traiter et leur complexité limitent grandement leur usage. Dans le même contexte, nous proposons de simplifier ces systèmes en remplaçant une caméra par une
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