Relevant bibliographies by topics / Deep Unsupervised Learning / Dissertations / Theses
To see the other types of publications on this topic, follow the link: Deep Unsupervised Learning.

Dissertations / Theses on the topic 'Deep Unsupervised Learning'

Author: Grafiati
Published: 6 September 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 dissertations / theses for your research on the topic 'Deep Unsupervised Learning.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

1

Drexler, Jennifer Fox. "Deep unsupervised learning from speech." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105696.

Full text
Abstract:
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 87-92).<br>Automatic speech recognition (ASR) systems have become hugely successful in recent years - we have become accustomed to speech interfaces across all kinds of devices. However, despite the huge impact ASR has had on the way we interact with technology, it is out of reach for a significant portion of the world's population. This is because these systems rely on a variety of manually-
APA, Harvard, Vancouver, ISO, and other styles
2

Ahn, Euijoon. "Unsupervised Deep Feature Learning for Medical Image Analysis." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23002.

Full text
Abstract:
The availability of annotated image datasets and recent advances in supervised deep learning methods are enabling the end-to-end derivation of representative image features that can impact a variety of image analysis problems. These supervised methods use prior knowledge derived from labelled training data and approaches, for example, convolutional neural networks (CNNs) have produced impressive results in natural (photographic) image classification. CNNs learn image features in a hierarchical fashion. Each deeper layer of the network learns a representation of the image data that is higher le
APA, Harvard, Vancouver, ISO, and other styles
3

Caron, Mathilde. "Unsupervised Representation Learning with Clustering in Deep Convolutional Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-227926.

Full text
Abstract:
This master thesis tackles the problem of unsupervised learning of visual representations with deep Convolutional Neural Networks (CNN). This is one of the main actual challenges in image recognition to close the gap between unsupervised and supervised representation learning. We propose a novel and simple way of training CNN on fully unlabeled datasets. Our method jointly optimizes a grouping of the representations and trains a CNN using the groups as supervision. We evaluate the models trained with our method on standard transfer learning experiments from the literature. We find out that our
APA, Harvard, Vancouver, ISO, and other styles
4

Manjunatha, Bharadwaj Sandhya. "Land Cover Quantification using Autoencoder based Unsupervised Deep Learning." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99861.

Full text
Abstract:
This work aims to develop a deep learning model for land cover quantification through hyperspectral unmixing using an unsupervised autoencoder. Land cover identification and classification is instrumental in urban planning, environmental monitoring and land management. With the technological advancements in remote sensing, hyperspectral imagery which captures high resolution images of the earth's surface across hundreds of wavelength bands, is becoming increasingly popular. The high spectral information in these images can be analyzed to identify the various target materials present in the ima
APA, Harvard, Vancouver, ISO, and other styles
5

Martin, Damien W. "Fault detection in manufacturing equipment using unsupervised deep learning." Thesis, Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/130698.

Full text
Abstract:
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021<br>Cataloged from the official PDF of thesis.<br>Includes bibliographical references (pages 87-90).<br>We investigate the use of unsupervised deep learning to create a general purpose automated fault detection system for manufacturing equipment. Unexpected equipment faults can be costly to manufacturing lines, but data driven fault detection systems often require a high level of application specific expertise to implement and continued human oversight. Collecting la
APA, Harvard, Vancouver, ISO, and other styles
6

Liu, Dongnan. "Supervised and Unsupervised Deep Learning-based Biomedical Image Segmentation." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/24744.

Full text
Abstract:
Biomedical image analysis plays a crucial role in the development of healthcare, with a wide scope of applications including the disease diagnosis, clinical treatment, and future prognosis. Among various biomedical image analysis techniques, segmentation is an essential step, which aims at assigning each pixel with labels of interest on the category and instance. At the early stage, the segmentation results were obtained via manual annotation, which is time-consuming and error-prone. Over the past few decades, hand-craft feature based methods have been proposed to segment the biomedical images
APA, Harvard, Vancouver, ISO, and other styles
7

Nasrin, Mst Shamima. "Pathological Image Analysis with Supervised and Unsupervised Deep Learning Approaches." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1620052562772676.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Wu, Xinheng. "A Deep Unsupervised Anomaly Detection Model for Automated Tumor Segmentation." Thesis, The University of Sydney, 2020. https://hdl.handle.net/2123/22502.

Full text
Abstract:
Many researches have been investigated to provide the computer aided diagnosis (CAD) automated tumor segmentation in various medical images, e.g., magnetic resonance (MR), computed tomography (CT) and positron-emission tomography (PET). The recent advances in automated tumor segmentation have been achieved by supervised deep learning (DL) methods trained on large labelled data to cover tumor variations. However, there is a scarcity in such training data due to the cost of labeling process. Thus, with insufficient training data, supervised DL methods have difficulty in generating effective feat
APA, Harvard, Vancouver, ISO, and other styles
9

Längkvist, Martin. "Modeling time-series with deep networks." Doctoral thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-39415.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Dekhtiar, Jonathan. "Deep Learning and unsupervised learning to automate visual inspection in the manufacturing industry." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2513.

Full text
Abstract:
La croissance exponentielle des besoins et moyens informatiques implique un besoin croissant d’automatisation des procédés industriels. Ce constat est en particulier visible pour l’inspection visuelle automatique sur ligne de production. Bien qu’étudiée depuis 1970, peine toujours à être appliquée à de larges échelles et à faible coûts. Les méthodes employées dépendent grandement de la disponibilité des experts métiers. Ce qui provoque inévitablement une augmentation des coûts et une réduction de la flexibilité des méthodes employées. Depuis 2012, les avancées dans le domaine associé à l’étude
APA, Harvard, Vancouver, ISO, and other styles
11

Boschini, Matteo. "Unsupervised Learning of Scene Flow." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16226/.

Full text
Abstract:
As Computer Vision-powered autonomous systems are increasingly deployed to solve problems in the wild, the case is made for developing visual understanding methods that are robust and flexible. One of the most challenging tasks for this purpose is given by the extraction of scene flow, that is the dense three-dimensional vector field that associates each world point with its corresponding position in the next observed frame, hence describing its three-dimensional motion entirely. The recent addition of a limited amount of ground truth scene flow information to the popular KITTI dataset prompt
APA, Harvard, Vancouver, ISO, and other styles
12

Feng, Zeyu. "Learning Deep Representations from Unlabelled Data for Visual Recognition." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/26876.

Full text
Abstract:
Self-supervised learning (SSL) aims at extracting from abundant unlabelled images transferable semantic features, which benefit various downstream visual tasks by reducing the sample complexity when human annotated labels are scarce. SSL is promising because it also boosts performance in diverse tasks when combined with the knowledge of existing techniques. Therefore, it is important and meaningful to study how SSL leads to better transferability and design novel SSL methods. To this end, this thesis proposes several methods to improve SSL and its function in downstream tasks. We begin by i
APA, Harvard, Vancouver, ISO, and other styles
13

Jiménez-Pérez, Guillermo. "Deep learning and unsupervised machine learning for the quantification and interpretation of electrocardiographic signals." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673555.

Full text
Abstract:
Las señales electrocardiográficas, ya sea adquiridas en la piel del paciente (electrocardiogamas de superficie, ECG) o de forma invasiva mediante cateterismo (electrocardiogramas intracavitarios, iECG) ayudan a explorar la condición y función cardíacas del paciente, dada su capacidad para representar la actividad eléctrica del corazón. Sin embargo, la interpretación de las señales de ECG e iECG es una tarea difícil que requiere años de experiencia, con criterios diagnósticos complejos para personal clínico no especialista, que en muchos casos deben ser interpretados durante situaciones
APA, Harvard, Vancouver, ISO, and other styles
14

De, Deuge Mark. "Manifold Learning Approaches to Compressing Latent Spaces of Unsupervised Feature Hierarchies." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14551.

Full text
Abstract:
Field robots encounter dynamic unstructured environments containing a vast array of unique objects. In order to make sense of the world in which they are placed, they collect large quantities of unlabelled data with a variety of sensors. Producing robust and reliable applications depends entirely on the ability of the robot to understand the unlabelled data it obtains. Deep Learning techniques have had a high level of success in learning powerful unsupervised representations for a variety of discriminative and generative models. Applying these techniques to problems encountered in field robot
APA, Harvard, Vancouver, ISO, and other styles
15

Varshney, Varun. "Supervised and unsupervised learning for plant and crop row detection in precision agriculture." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/35463.

Full text
Abstract:
Master of Science<br>Department of Computing and Information Sciences<br>William H. Hsu<br>The goal of this research is to present a comparison between different clustering and segmentation techniques, both supervised and unsupervised, to detect plant and crop rows. Aerial images, taken by an Unmanned Aerial Vehicle (UAV), of a corn field at various stages of growth were acquired in RGB format through the Agronomy Department at the Kansas State University. Several segmentation and clustering approaches were applied to these images, namely K-Means clustering, Excessive Green (ExG) Index algorit
APA, Harvard, Vancouver, ISO, and other styles
16

Sahasrabudhe, Mihir. "Unsupervised and weakly supervised deep learning methods for computer vision and medical imaging." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASC010.

Full text
Abstract:
Les premières contributions de cette thèse (Chapter 2 et Chapitre 3) sont des modèles appelés Deforming Autoencoder (DAE) et Lifting Autoencoder (LAE), utilisés pour l'apprentissage non-supervisé de l'alignement 2-D dense d'images d'une classe donnée, et à partir de cela, pour apprendre un modèle tridimensionnel de l'objet. Ces modèles sont capable d'identifer des espaces canoniques pour représenter de différent caractéristiques de l'objet, à savoir, l'apparence des objets dans l'espace canonique, la déformation dense associée permettant de retrouver l'image réelle à partir de cette apparence,
APA, Harvard, Vancouver, ISO, and other styles
17

Landi, Isotta. "Stratification of autism spectrum conditions by deep encodings." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/252684.

Full text
Abstract:
This work aims at developing a novel machine learning method to investigate heterogeneity in neurodevelopmental disorders, with a focus on autism spectrum conditions (ASCs). In ASCs, heterogeneity is shown at several levels of analysis, e.g., genetic, behavioral, throughout developmental trajectories, which hinders the development of effective treatments and the identification of biological pathways involved in gene-cognition-behavior links. ASC diagnosis comes from behavioral observations, which determine the cohort composition of studies in every scientific field (e.g., psychology, neuro
APA, Harvard, Vancouver, ISO, and other styles
18

Landi, Isotta. "Stratification of autism spectrum conditions by deep encodings." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/252684.

Full text
Abstract:
This work aims at developing a novel machine learning method to investigate heterogeneity in neurodevelopmental disorders, with a focus on autism spectrum conditions (ASCs). In ASCs, heterogeneity is shown at several levels of analysis, e.g., genetic, behavioral, throughout developmental trajectories, which hinders the development of effective treatments and the identification of biological pathways involved in gene-cognition-behavior links. ASC diagnosis comes from behavioral observations, which determine the cohort composition of studies in every scientific field (e.g., psychology, neuro
APA, Harvard, Vancouver, ISO, and other styles
19

Larsson, Frans. "Algorithmic trading surveillance : Identifying deviating behavior with unsupervised anomaly detection." Thesis, Uppsala universitet, Matematiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-389941.

Full text
Abstract:
The financial markets are no longer what they used to be and one reason for this is the breakthrough of algorithmic trading. Although this has had several positive effects, there have been recorded incidents where algorithms have been involved. It is therefore of interest to find effective methods to monitor algorithmic trading. The purpose of this thesis was therefore to contribute to this research area by investigating if machine learning can be used for detecting deviating behavior. Since the real world data set used in this study lacked labels, an unsupervised anomaly detection approach wa
APA, Harvard, Vancouver, ISO, and other styles
20

Merrill, Nicholas Swede. "Modified Kernel Principal Component Analysis and Autoencoder Approaches to Unsupervised Anomaly Detection." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98659.

Full text
Abstract:
Unsupervised anomaly detection is the task of identifying examples that differ from the normal or expected pattern without the use of labeled training data. Our research addresses shortcomings in two existing anomaly detection algorithms, Kernel Principal Component Analysis (KPCA) and Autoencoders (AE), and proposes novel solutions to improve both of their performances in the unsupervised settings. Anomaly detection has several useful applications, such as intrusion detection, fault monitoring, and vision processing. More specifically, anomaly detection can be used in autonomous driving to ide
APA, Harvard, Vancouver, ISO, and other styles
21

ABUKMEIL, MOHANAD. "UNSUPERVISED GENERATIVE MODELS FOR DATA ANALYSIS AND EXPLAINABLE ARTIFICIAL INTELLIGENCE." Doctoral thesis, Università degli Studi di Milano, 2022. http://hdl.handle.net/2434/889159.

Full text
Abstract:
For more than a century, the methods of learning representation and the exploration of the intrinsic structures of data have developed remarkably and currently include supervised, semi-supervised, and unsupervised methods. However, recent years have witnessed the flourishing of big data, where typical dataset dimensions are high, and the data can come in messy, missing, incomplete, unlabeled, or corrupted forms. Consequently, discovering and learning the hidden structure buried inside such data becomes highly challenging. From this perspective, latent data analysis and dimensionality reductio
APA, Harvard, Vancouver, ISO, and other styles
22

Olsson, Sebastian. "Automated sleep scoring using unsupervised learning of meta-features." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189234.

Full text
Abstract:
Sleep is an important part of life as it affects the performance of one's activities during all awake hours. The study of sleep and wakefulness is therefore of great interest, particularly to the clinical and medical fields where sleep disorders are diagnosed. When studying sleep, it is common to talk about different types, or stages, of sleep. A common task in sleep research is to determine the sleep stage of the sleeping subject as a function of time. This process is known as sleep stage scoring. In this study, I seek to determine whether there is any benefit to using unsupervised feature le
APA, Harvard, Vancouver, ISO, and other styles
23

Budaraju, Sri Datta. "Unsupervised 3D Human Pose Estimation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291435.

Full text
Abstract:
The thesis proposes an unsupervised representation learning method to predict 3D human pose from a 2D skeleton via a VAEGAN (Variational Autoencoder Generative Adversarial Network) hybrid network. The method learns to lift poses from 2D to 3D using selfsupervision and adversarial learning techniques. The method does not use images, heatmaps, 3D pose annotations, paired/unpaired 2Dto3D skeletons, 3D priors, synthetic 2D skeletons, multiview or temporal information in any shape or form. The 2D skeleton input is taken by a VAE that encodes it in a latent space and then decodes that latent represe
APA, Harvard, Vancouver, ISO, and other styles
24

Lind, Johan. "Evaluating CNN-based models for unsupervised image denoising." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176092.

Full text
Abstract:
Images are often corrupted by noise which reduces their visual quality and interferes with analysis. Convolutional Neural Networks (CNNs) have become a popular method for denoising images, but their training typically relies on access to thousands of pairs of noisy and clean versions of the same underlying picture. Unsupervised methods lack this requirement and can instead be trained purely using noisy images. This thesis evaluated two different unsupervised denoising algorithms: Noise2Self (N2S) and Parametric Probabilistic Noise2Void (PPN2V), both of which train an internal CNN to denoise im
APA, Harvard, Vancouver, ISO, and other styles
25

Farouni, Tarek. "An Overview of Probabilistic Latent Variable Models with anApplication to the Deep Unsupervised Learning of ChromatinStates." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492189894812539.

Full text
APA, Harvard, Vancouver, ISO, and other styles
26

Bujwid, Sebastian. "GANtruth – a regularization method for unsupervised image-to-image translation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233849.

Full text
Abstract:
In this work, we propose a novel and effective method for constraining the output space of the ill-posed problem of unsupervised image-to-image translation. We make the assumption that the environment of the source domain is known, and we propose to explicitly enforce preservation of the ground-truth labels on the images translated from the source to the target domain. We run empirical experiments on preserving information such as semantic segmentation and disparity and show evidence that our method achieves improved performance over the baseline model UNIT on translating images from SYNTHIA t
APA, Harvard, Vancouver, ISO, and other styles
27

Anand, Gaurangi. "Unsupervised visual perception-based representation learning for time-series and trajectories." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/212901/1/Gaurangi_Anand_Thesis.pdf.

Full text
Abstract:
Representing time-series without relying on the domain knowledge and independent of the end-task is a challenging problem. The same situation applies to trajectory data as well, where sufficient labelled information is often unavailable to learn effective representations. This thesis addresses this problem and explores unsupervised ways of representing the temporal data. The novel methods imitate the human visual perception of the pictorial depiction of such data based on deep learning.
APA, Harvard, Vancouver, ISO, and other styles
28

Ackerman, Wesley. "Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8684.

Full text
Abstract:
We expand the scope of image-to-image translation to include more distinct image domains, where the image sets have analogous structures, but may not share object types between them. Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains (SUNIT) is built to more successfully translate images in this setting, where content from one domain is not found in the other. Our method trains an image translation model by learning encodings for semantic segmentations of images. These segmentations are translated between image domains to learn meaningful mappings between the st
APA, Harvard, Vancouver, ISO, and other styles
29

Mehr, Éloi. "Unsupervised Learning of 3D Shape Spaces for 3D Modeling." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS566.

Full text
Abstract:
Bien que les données 3D soient de plus en plus populaires, en particulier avec la démocratisation des expériences de réalité virtuelle et augmentée, il reste très difficile de manipuler une forme 3D, même pour des designers ou des experts. Partant d’une base de données d’instances 3D d’une ou plusieurs catégories d’objets, nous voulons apprendre la variété des formes plausibles en vue de développer de nouveaux outils intelligents de modélisation et d’édition 3D. Cependant, cette variété est souvent bien plus complexe comparée au domaine 2D. En effet, les surfaces 3D peuvent être représentées e
APA, Harvard, Vancouver, ISO, and other styles
30

McClintick, Kyle W. "Training Data Generation Framework For Machine-Learning Based Classifiers." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-theses/1276.

Full text
Abstract:
In this thesis, we propose a new framework for the generation of training data for machine learning techniques used for classification in communications applications. Machine learning-based signal classifiers do not generalize well when training data does not describe the underlying probability distribution of real signals. The simplest way to accomplish statistical similarity between training and testing data is to synthesize training data passed through a permutation of plausible forms of noise. To accomplish this, a framework is proposed that implements arbitrary channel conditions and base
APA, Harvard, Vancouver, ISO, and other styles
31

Marchesin, Stefano. "Developing unsupervised knowledge-enhanced models to reduce the semantic Gap in information retrieval." Doctoral thesis, Università degli studi di Padova, 2020. http://hdl.handle.net/11577/3426253.

Full text
Abstract:
In this thesis we tackle the semantic gap, a long-standing problem in Information Retrieval(IR). The semantic gap can be described as the mismatch between users’ queries and the way retrieval models answer to such queries. Two main lines of work have emerged over the years to bridge the semantic gap: (i) the use of external knowledge resources to enhance the bag-of-words representations used by lexical models, and (ii) the use of semantic models to perform matching between the latent representations of queries and documents. To deal with this issue, we first perform an in-depth evaluation of l
APA, Harvard, Vancouver, ISO, and other styles
32

Li, Yingzhen. "Approximate inference : new visions." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/277549.

Full text
Abstract:
Nowadays machine learning (especially deep learning) techniques are being incorporated to many intelligent systems affecting the quality of human life. The ultimate purpose of these systems is to perform automated decision making, and in order to achieve this, predictive systems need to return estimates of their confidence. Powered by the rules of probability, Bayesian inference is the gold standard method to perform coherent reasoning under uncertainty. It is generally believed that intelligent systems following the Bayesian approach can better incorporate uncertainty information for reliable
APA, Harvard, Vancouver, ISO, and other styles
33

Andraghetti, Lorenzo. "Monocular Depth Estimation enhancement by depth from SLAM Keypoints." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16626/.

Full text
Abstract:
Training a neural network in a supervised way is extremely challenging since ground truth is expensive, time consuming and limited. Therefore the best choice is to do it unsupervisedly, exploiting easier-to-obtain binocular stereo images and epipolar geometry constraints. Sometimes however, this is not enough to predict fairly correct depth maps because of ambiguity of colour images, due for instance to shadows, reflective surfaces and so on. A Simultaneous Location and Mapping (SLAM) algorithm keeps track of hundreds of 3D landmarks in each frame of a sequence. Therefore, given the base assu
APA, Harvard, Vancouver, ISO, and other styles
34

Kilinc, Ismail Ozsel. "Graph-based Latent Embedding, Annotation and Representation Learning in Neural Networks for Semi-supervised and Unsupervised Settings." Scholar Commons, 2017. https://scholarcommons.usf.edu/etd/7415.

Full text
Abstract:
Machine learning has been immensely successful in supervised learning with outstanding examples in major industrial applications such as voice and image recognition. Following these developments, the most recent research has now begun to focus primarily on algorithms which can exploit very large sets of unlabeled examples to reduce the amount of manually labeled data required for existing models to perform well. In this dissertation, we propose graph-based latent embedding/annotation/representation learning techniques in neural networks tailored for semi-supervised and uns
APA, Harvard, Vancouver, ISO, and other styles
35

Guiraud, Enrico [Verfasser], Jörg [Akademischer Betreuer] Lücke, and Ralf [Akademischer Betreuer] Häfner. "Scalable unsupervised learning for deep discrete generative models: novel variational algorithms and their software realizations / Enrico Guiraud ; Jörg Lücke, Ralf Häfner." Oldenburg : BIS der Universität Oldenburg, 2020. http://d-nb.info/1226287077/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
36

Baur, Christoph [Verfasser], Nassir [Akademischer Betreuer] Navab, Nassir [Gutachter] Navab, and Ben [Gutachter] Glocker. "Anomaly Detection in Brain MRI: From Supervised to Unsupervised Deep Learning / Christoph Baur ; Gutachter: Nassir Navab, Ben Glocker ; Betreuer: Nassir Navab." München : Universitätsbibliothek der TU München, 2021. http://d-nb.info/1236343115/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
37

Cherti, Mehdi. "Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS029/document.

Full text
Abstract:
Des avancées significatives sur les réseaux de neurones profonds ont récemment permis le développement de technologies importantes comme les voitures autonomes et les assistants personnels intelligents basés sur la commande vocale. La plupart des succès en apprentissage profond concernent la prédiction, alors que les percées initiales viennent des modèles génératifs. Actuellement, même s'il existe des outils puissants dans la littérature des modèles génératifs basés sur les réseaux profonds, ces techniques sont essentiellement utilisées pour la prédiction ou pour générer des objets connus (i.e
APA, Harvard, Vancouver, ISO, and other styles
38

Juan, Albarracín Javier. "Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature." Doctoral thesis, Universitat Politècnica de València, 2020. http://hdl.handle.net/10251/149560.

Full text
Abstract:
[ES] El futuro de la imagen médica está ligado a la inteligencia artificial. El análisis manual de imágenes médicas es hoy en día una tarea ardua, propensa a errores y a menudo inasequible para los humanos, que ha llamado la atención de la comunidad de Aprendizaje Automático (AA). La Imagen por Resonancia Magnética (IRM) nos proporciona una rica variedad de representaciones de la morfología y el comportamiento de lesiones inaccesibles sin una intervención invasiva arriesgada. Sin embargo, explotar la potente pero a menudo latente información contenida en la IRM es una tarea muy complicada, que
APA, Harvard, Vancouver, ISO, and other styles
39

Donati, Lorenzo. "Domain Adaptation through Deep Neural Networks for Health Informatics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14888/.

Full text
Abstract:
The PreventIT project is an EU Horizon 2020 project aimed at preventing early functional decline at younger old age. The analysis of causal links between risk factors and functional decline has been made possible by the cooperation of several research institutes' studies. However, since each research institute collects and delivers different kinds of data in different formats, so far the analysis has been assisted by expert geriatricians whose role is to detect the best candidates among hundreds of fields and offer a semantic interpretation of the values. This manual data harmonization approac
APA, Harvard, Vancouver, ISO, and other styles
40

Espis, Andrea. "Object detection and semantic segmentation for assisted data labeling." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

Find full text
Abstract:
The automation of data labeling tasks is a solution to the errors and time costs related to human labeling. In this thesis work CenterNet, DeepLabV3, and K-Means applied to the RGB color space, are deployed to build a pipeline for Assisted data labeling: a semi-automatic process to iteratively improve the quality of the annotations. The proposed pipeline pointed out a total of 1547 wrong and missing annotations when applied to a dataset originally containing 8,300 annotations. Moreover, the quality of each annotation has been drastically improved, and at the same time, more than 600 hours of w
APA, Harvard, Vancouver, ISO, and other styles
41

ZHU, XIANGPING. "Learning Discriminative Features for Person Re-Identification." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/997742.

Full text
Abstract:
For fulfilling the requirements of public safety in modern cities, more and more large-scale surveillance camera systems are deployed, resulting in an enormous amount of visual data. Automatically processing and interpreting these data promote the development and application of visual data analytic technologies. As one of the important research topics in surveillance systems, person re-identification (re-id) aims at retrieving the target person across non-overlapping camera-views that are implemented in a number of distributed space-time locations. It is a fundamental problem for many practica
APA, Harvard, Vancouver, ISO, and other styles
42

Carlsson, Filip, and Philip Lindgren. "Deep Scenario Generation of Financial Markets." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273631.

Full text
Abstract:
The goal of this thesis is to explore a new clustering algorithm, VAE-Clustering, and examine if it can be applied to find differences in the distribution of stock returns and augment the distribution of a current portfolio of stocks and see how it performs in different market conditions. The VAE-clustering method is as mentioned a newly introduced method and not widely tested, especially not on time series. The first step is therefore to see if and how well the clustering works. We first apply the algorithm to a dataset containing monthly time series of the power demand in Italy. The purpose
APA, Harvard, Vancouver, ISO, and other styles
43

Choi, Jin-Woo. "Action Recognition with Knowledge Transfer." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/101780.

Full text
Abstract:
Recent progress on deep neural networks has shown remarkable action recognition performance from videos. The remarkable performance is often achieved by transfer learning: training a model on a large-scale labeled dataset (source) and then fine-tuning the model on the small-scale labeled datasets (targets). However, existing action recognition models do not always generalize well on new tasks or datasets because of the following two reasons. i) Current action recognition datasets have a spurious correlation between action types and background scene types. The models trained on these datasets a
APA, Harvard, Vancouver, ISO, and other styles
44

Alise, Dario Fioravante. "Algoritmo di "Label Propagation" per il clustering di documenti testuali." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14388/.

Full text
Abstract:
Negli ultimi anni del secolo scorso l’avvento di Internet ha permesso di avere a disposizione innumerevoli quantità di testi consultabili online, provenienti sia da libri e riviste, sia da nuove forme di comunicazione della rete quali email, forum, newsgroup e chat. 
Le soluzioni adottate nel settore del Text Mining (d’ora in poi abbreviato in TM), che è l’estensione del Data Mining rivolto a dati testuali non strutturati, si basano su fondamenti informatici, statistici e linguistici e sono in linea di principio applicabili a documenti di qualsiasi dimensione.
Con l’avvento dei Social Networks
APA, Harvard, Vancouver, ISO, and other styles
45

Yuan, Xiao. "Graph neural networks for spatial gene expression analysis of the developing human heart." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-427330.

Full text
Abstract:
Single-cell RNA sequencing and in situ sequencing were combined in a recent study of the developing human heart to explore the transcriptional landscape at three developmental stages. However, the method used in the study to create the spatial cellular maps has some limitations. It relies on image segmentation of the nuclei and cell types defined in advance by single-cell sequencing. In this study, we applied a new unsupervised approach based on graph neural networks on the in situ sequencing data of the human heart to find spatial gene expression patterns and detect novel cell and sub-cell ty
APA, Harvard, Vancouver, ISO, and other styles
46

Chafaa, Irched. "Machine learning for beam alignment in mmWave networks." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG044.

Full text
Abstract:
Pour faire face à la croissance exponentielle du trafic des données mobiles, une solution possible est d'exploiter les larges bandes spectrales disponibles dans la partie millimétrique du spectre électromagnétique. Cependant, le signal transmis est fortement atténué, impliquant une portée de propagation limitée et un faible nombre des trajets de propagation (canal parcimonieux). Par conséquent, des faisceaux directifs doivent être utilisés pour focaliser l'énergie du signal transmis vers son utilisateur et compenser les pertes de propagation. Ces faisceaux ont besoin d'être dirigés convenablem
APA, Harvard, Vancouver, ISO, and other styles
47

Sjökvist, Henrik. "Text feature mining using pre-trained word embeddings." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228536.

Full text
Abstract:
This thesis explores a machine learning task where the data contains not only numerical features but also free-text features. In order to employ a supervised classifier and make predictions, the free-text features must be converted into numerical features.  In this thesis, an algorithm is developed to perform that conversion. The algorithm uses a pre-trained word embedding model which maps each word to a vector. The vectors for multiple word embeddings belonging to the same sentence are then combined to form a single sentence embedding. The sentence embeddings for the whole dataset are cluster
APA, Harvard, Vancouver, ISO, and other styles
48

Yogeswaran, Arjun. "Self-Organizing Neural Visual Models to Learn Feature Detectors and Motion Tracking Behaviour by Exposure to Real-World Data." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37096.

Full text
Abstract:
Advances in unsupervised learning and deep neural networks have led to increased performance in a number of domains, and to the ability to draw strong comparisons between the biological method of self-organization conducted by the brain and computational mechanisms. This thesis aims to use real-world data to tackle two areas in the domain of computer vision which have biological equivalents: feature detection and motion tracking. The aforementioned advances have allowed efficient learning of feature representations directly from large sets of unlabeled data instead of using traditional handcr
APA, Harvard, Vancouver, ISO, and other styles
49

Chafik, Sanaa. "Machine learning techniques for content-based information retrieval." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL008/document.

Full text
Abstract:
Avec l’évolution des technologies numériques et la prolifération d'internet, la quantité d’information numérique a considérablement évolué. La recherche par similarité (ou recherche des plus proches voisins) est une problématique que plusieurs communautés de recherche ont tenté de résoudre. Les systèmes de recherche par le contenu de l’information constituent l’une des solutions prometteuses à ce problème. Ces systèmes sont composés essentiellement de trois unités fondamentales, une unité de représentation des données pour l’extraction des primitives, une unité d’indexation multidimensionnelle
APA, Harvard, Vancouver, ISO, and other styles
50

Sala, Cardoso Enric. "Advanced energy management strategies for HVAC systems in smart buildings." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/668528.

Full text
Abstract:
The efficacy of the energy management systems at dealing with energy consumption in buildings has been a topic with a growing interest in recent years due to the ever-increasing global energy demand and the large percentage of energy being currently used by buildings. The scale of this sector has attracted research effort with the objective of uncovering potential improvement avenues and materializing them with the help of recent technological advances that could be exploited to lower the energetic footprint of buildings. Specifically, in the area of heating, ventilating and air conditioning i
APA, Harvard, Vancouver, ISO, and other styles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography