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Relevant bibliographies by topics / Dataset annotation / Dissertations / Theses

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Dissertations / Theses on the topic 'Dataset annotation'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Herbst, Alyssa Kathryn. "Bounded Expectation of Label Assignment: Dataset Annotation by Supervised Splitting with Bias-Reduction Techniques." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/96517.

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Annotating large unlabeled datasets can be a major bottleneck for machine learning applications. We introduce a scheme for inferring labels of unlabeled data at a fraction of the cost of labeling the entire dataset. We refer to the scheme as Bounded Expectation of Label Assignment (BELA). BELA greedily queries an oracle (or human labeler) and partitions a dataset to find data subsets that have mostly the same label. BELA can then infer labels by majority vote of the known labels in each subset. BELA makes the decision to split or label from a subset by maximizing a lower bound on the expected

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2

Mezírka, Martin. "Pokročilé metody detekce hran v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234883.

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The goal of this work is to investigate options how to apply trainable edge detection algorithm Structured forest for fast edge detection to information extraction from historici maps and medical images. For the work, annotated dataset was created and the detektor was tested on it. Structured forest achieved better results on map data, compared with classical detectors. Success rate of finding edges of bones was similar at both approaches. Aim of the work is focused on comparing different image annotation styles, experiments with dataset, including determining parameters and evaluation of the

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3

Tagebrand, Emil, and Ek Emil Gustafsson. "Dataset Generation in a Simulated Environment Using Real Flight Data for Reliable Runway Detection Capabilities." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54974.

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Implementing object detection methods for runway detection during landing approaches is limited in the safety-critical aircraft domain. This limitation is due to the difficulty that comes with verification of the design and the ability to understand how the object detection behaves during operation. During operation, object detection needs to consider the aircraft's position, environmental factors, different runways and aircraft attitudes. Training such an object detection model requires a comprehensive dataset that defines the features mentioned above. The feature's impact on the detection ca

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4

ALZETTA, CHIARA. "From Texts to Prerequisites. Identifying and Annotating Propaedeutic Relations in Educational Textual Resources." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1050378.

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Prerequisite Relations (PRs) are dependency relations established between two distinct concepts expressing which piece(s) of information a student has to learn first in order to understand a certain target concept. Such relations are one of the most fundamental in Education, playing a crucial role not only for what concerns new knowledge acquisition, but also in the novel applications of Artificial Intelligence to distant and e-learning. Indeed, resources annotated with such information could be used to develop automatic systems able to acquire and organize the knowledge embodied in educationa

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5

Zhang, Ao. "Object Detection from FMCW Radar Using Deep Learning." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42512.

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Sensors, as a crucial part of autonomous driving, are primarily used for perceiving the environment. The recent deep learning development of different sensors has demonstrated the ability of machines recognizing and understanding their surroundings. Automotive radar, as a primary sensor for self-driving vehicles, is well-known for its robustness against variable lighting and weather conditions. Compared with camera-based deep learning development, Object detection using automotive radars has not been explored to its full extent. This can be attributed to the lack of public radar datasets. I

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6

Mahmood, Muhammad Habib. "Motion annotation in complex video datasets." Doctoral thesis, Universitat de Girona, 2018. http://hdl.handle.net/10803/667583.

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Motion segmentation refers to the process of separating regions and trajectories from a video sequence into coherent subsets of space and time. In this thesis, we created a new multifaceted motion segmentation dataset enclosing real-life long and short sequences, with different numbers of motions and frames per sequence, and real distortions with missing data. Trajectory- and region-based ground-truth is provided on all the frames of all the sequences. We also proposed a new semi-automatic tool for delineating the trajectories in complex videos, even in videos captured from moving cameras. Wit

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7

Csóka, Pavel. "Rozpoznávání textu pomocí konvolučních sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255303.

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This thesis aims at creation of new datasets for text recognition machine learning tasks and experiments with convolutional neural networks on these datasets. It describes architecture of convolutional nets, difficulties of recognizing text from photographs and contemporary works using these networks. Next, creation of annotation, using Tesseract OCR, for dataset comprised from photos of document pages, taken by mobile phones, named Mobile Page Photos. From this dataset two additional are created by cropping characters out of its photos formatted as Street View House Numbers dataset. Dataset M

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8

Li, Jin. "Constructing classification trees with exception annotations for large datasets." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0027/MQ51392.pdf.

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9

Romuld, Daniel, and Markus Ruhmén. "Compiling attention datasets : Developing a method for annotating face datasets with human performance attention labels using crowdsourcing." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166708.

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This essay expands on the problem of human attention detection in computer vision. This is achieved by providing a method for annotating existing face datasets with attention labels through the use of human intelligence. The work described in this essay is justified by a lack of human performance attention datasets and the potential uses of the developed method. Several images of crowds were generated using the Labeled Faces in the Wild dataset of images depicting faces. Thus enabling evaluation of the level of attention of the depicted subjects as part of a crowd. The data collection methodol

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10

Liu, Jixiong. "Semantic Annotations for Tabular Data Using Embeddings : Application to Datasets Indexing and Table Augmentation." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS529.

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Avec le développement de l'Open Data, un grand nombre de sources de données sont mises à disposition des communautés (notamment les data scientists et les data analysts). Ces données constituent des sources importantes pour les services numériques sous réserve que les données soient nettoyées, non biaisées, et combinées à une sémantique explicite et compréhensible par les algorithmes afin de favoriser leur exploitation. En particulier, les sources de données structurées (CSV, JSON, XML, etc.) constituent la matière première de nombreux processus de science des données. Cependant, ces données p

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11

Wodke, Judith. "Organization and integration of large-scale datasets for designing a metabolic model and re-annotating the genome of mycoplasma pneumoniae." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://dx.doi.org/10.18452/16699.

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Mycoplasma pneumoniae, einer der kleinsten lebenden Organismen, ist ein erfolgversprechender Modellorganismus der Systembiologie um eine komplette lebende Zelle zu verstehen. Wichtig dahingehend ist die Konstruktion mathematischer Modelle, die zelluläre Prozesse beschreiben, indem sie beteiligte Komponenten vernetzen und zugrundeliegende Mechanismen entschlüsseln. Für Mycoplasma pneumoniae wurden genomweite Datensätze für Genomics, Transcriptomics, Proteomics und Metabolomics produziert. Allerdings fehlten ein effizientes Informationsaustauschsystem und mathematische Modelle zur Datenintegrati

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12

Meléndez, Catalán Blai. "Relative music loudness estimation in TV broadcast audio using deep learning: an industrial perspective." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671425.

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Under the current copyright management business model, broadcasters are taxed by the corresponding copyright management organization according to the percentage of music they broadcast, and the collected money is then distributed among the copyright holders of that music. In the specific case of TV broadcasts, whether a musical piece is played in the foreground or the background is often a relevant factor that affects the amount of money collected and distributed. In recent years, the music industry is increasingly adopting technological solutions to automatize this process. We have conducted

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13

Wodke, Judith [Verfasser], Edda [Akademischer Betreuer] Klipp, Luís [Akademischer Betreuer] Serrano, and Hermann-Georg [Akademischer Betreuer] Holzhütter. "Organization and integration of large-scale datasets for designing a metabolic model and re-annotating the genome of mycoplasma pneumoniae : an application of the systems biology approach to a minimal bacterium / Judith Wodke. Gutachter: Edda Klipp ; Luis Serrano ; Hermann-Georg Holzhütter." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://d-nb.info/1032944242/34.

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14

Wodke, Judith Andrea Heidrun [Verfasser], Edda [Akademischer Betreuer] Klipp, Luís [Akademischer Betreuer] Serrano, and Hermann-Georg [Akademischer Betreuer] Holzhütter. "Organization and integration of large-scale datasets for designing a metabolic model and re-annotating the genome of mycoplasma pneumoniae : an application of the systems biology approach to a minimal bacterium / Judith Wodke. Gutachter: Edda Klipp ; Luis Serrano ; Hermann-Georg Holzhütter." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://nbn-resolving.de/urn:nbn:de:kobv:11-100207899.

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15

Fortuna, Paula Cristina Teixeira. "Automatic detection of hate speech in text: an overview of the topic and dataset annotation with hierarchical classes." Master's thesis, 2017. https://repositorio-aberto.up.pt/handle/10216/106028.

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Nowadays people are using more and more social networks to communicate their opinions, share information and experiences. In social networks people have the feeling of being deindividualized and can incur more frequently in aggressive communication. In this context, it is important that government and social networks platforms have tools to detect hate speech because it is harmful to its targets. In our work we investigate the problem of detecting hate speech online. Our first goal is to make a complete overview on the topic. However, describing the state of the art in the area of hate speech

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16

Fortuna, Paula Cristina Teixeira. "Automatic detection of hate speech in text: an overview of the topic and dataset annotation with hierarchical classes." Dissertação, 2017. https://repositorio-aberto.up.pt/handle/10216/106028.

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Nowadays people are using more and more social networks to communicate their opinions, share information and experiences. In social networks people have the feeling of being deindividualized and can incur more frequently in aggressive communication. In this context, it is important that government and social networks platforms have tools to detect hate speech because it is harmful to its targets. In our work we investigate the problem of detecting hate speech online. Our first goal is to make a complete overview on the topic. However, describing the state of the art in the area of hate speech

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17

Castro, Sérgio Ricardo de. "Developing reliability metrics and validation tools for datasets with deep linguistic information." Master's thesis, 2011. http://hdl.handle.net/10451/13908.

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The purpose of this dissertation is to propose a reliability metric and respective validation tools for corpora annotated with deep linguistic information. The annotation of corpus with deep linguistic information is a complex task, and therefore is aided by a computational grammar. This grammar generates all the possible grammatical representations for sentences. The human annotators select the most correct analysis for each sentence, or reject it if no suitable representation is achieved. This task is repeated by two human annotators under a double-blind annotation scheme and the resulting a

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18

Amelio, Ravelli Andrea. "Annotation of Linguistically Derived Action Concepts in Computer Vision Datasets." Doctoral thesis, 2020. http://hdl.handle.net/2158/1200356.

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In the present work, an in-depth exploration of IMAGACT Ontology of Action Verbs has been traced, with the focus of exploiting the resource in NLP tasks. Starting from the Introduction, the idea of making use of IMAGACT multimodal action conceptualisation has been drawn, with some reflections on evidences of the deep linking between Language and Vision, and on the fact that action plays a key role in this linkage. Thus, the multimodal and multilingual features of IMAGACT have been described, with also some details on the framework of the resource building. It followed a concrete case-study on

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19

Breslav, Mikhail. "3D pose estimation of flying animals in multi-view video datasets." Thesis, 2016. https://hdl.handle.net/2144/19720.

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Flying animals such as bats, birds, and moths are actively studied by researchers wanting to better understand these animals’ behavior and flight characteristics. Towards this goal, multi-view videos of flying animals have been recorded both in lab- oratory conditions and natural habitats. The analysis of these videos has shifted over time from manual inspection by scientists to more automated and quantitative approaches based on computer vision algorithms. This thesis describes a study on the largely unexplored problem of 3D pose estimation of flying animals in multi-view video data. This

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