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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 80 1 Program Logic for Weak Memory Concurrency ... Doko, Marko. - : Technische Universität Kaiserslautern, 2021 BASE Show details 2 Neural Network Learning for Robust Speech Recognition Qu, Leyuan. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2021 BASE Show details 3 Student Performance and Collaboration in Introductory Courses to Theory of Computation ; Studierendenperformance und Kollaboration in Einführungskursen der Theoretischen Informatik Frede, Christiane. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2021 BASE Show details 4 Classifying user information needs in cooking dialogues – an empirical performance evaluation of transformer networks Schwabl, Patrick. - 2021 BASE Show details 5 Entwicklung und Evaluation eines Tools zur lexikonbasierten Sentiment Analysis für die Digital Humanities Dangel, Johanna. - 2021 BASE Show details 6 Language representations for computational argumentation Lauscher, Anne. - 2021 BASE Show details 7 Accessible digital documentary heritage : guidelines for the preparation of documentary heritage in accessible formats for persons with disabilities ... Darvishy, Alireza; Manning, Juliet. - : UNESCO, 2020 BASE Show details 8 Erfahrung und Gewissheit – Orientierungen in den Wissenschaften und im Alltag. IV. Regensburger Symposium vom 24.-26. März 2011 ... Thim-Mabrey, Christiane; Brack, Matthias. - : Universität Regensburg, 2020 BASE Show details 9 Conversational Language Learning for Human-Robot Interaction Bothe, Chandrakant Ramesh. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020 BASE Show details 10 Natural Language Visual Grounding via Multimodal Learning ; Natürliche Sprache Visual Grounding durch multimodales Lernen Mi, Jinpeng. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020 Abstract: Natural language provides an intuitive and effective interaction interface between human beings and intelligent agents. Currently, multiple approaches have been proposed to address natural language visual grounding. However, most of the existing approaches alleviate the ambiguity of natural language queries and achieve target objects grounding by drawing support from auxiliary information, such as dialogues between human users, and gestures. While the auxiliary information-based systems usually make the natural language grounding cumbersome and time-consuming. This thesis aims to study and exploit multimodal learning approaches for natural language visual grounding. Inspired by the pattern of human beings understanding and grounding target objects according to given natural language queries, we propose different architectures to address natural language visual grounding. First, we propose a semantic-aware network for referring expression comprehension which aims to locate the most relevant objects in images given natural referring expressions. The proposed referring expression comprehension network excavates the visual semantics in images via a visual semantic-aware network, exploits the rich linguistic contexts in referring expressions by a language attention network, and locates target objects by integrating the outputs of the visual semantic-aware network and the language attention network. Moreover, we conduct extensive experiments on three public datasets to validate the performance of the presented network. Second, we present a Generative Adversarial Networks-based network to generate diverse and natural referring expressions. Referring expression generation mimics the role of a speaker to generate referring expressions for each detected region within images. For this task, we aim to improve the diversity and naturalness of expressions without sacrificing semantic validity. To this end, we propose a generator to generate expressions and exploit a discriminator to classify whether the generated descriptions are real or fake. We evaluate the performance of the proposed generation network via multiple evaluation metrics. Third, inspired by the psychology term “affordance” and its applications in Human-Robot interaction, we draw support from object affordance to ground intention-related natural language queries. Formally, we first present an attention-based multi-visual features fusion network to recognize object affordances. The proposed network fuses deep visual features extracted from a pretrained CNN model with deep texture features encoded by a deep texture encoding network via an attention-based mechanism. We train and validate the performance of the object affordance detection network on a self-built dataset. Moreover, we propose three natural language visual grounding architectures, which are based on referring expression comprehension, referring expression generation, and object affordance detection, respectively. We combine the referring expression comprehension and referring expression generation models with scene graph parsing to achieve complicated and unconstrained natural language queries grounding. Additionally, we integrate the object affordance detection network with an intention semantic extraction module and a target grounding module to ground intention-related natural language queries. Finally, we implement extensive experiments to validate the effectiveness of the presented natural language visual grounding architectures. We also integrate with an online speech recognizer to complete target object grounding and manipulation experiments on a PR2 robot given spoken natural language commands. Keyword: 004 Informatik; 54.72 Künstliche Intelligenz; ddc:004 URL: http://nbn-resolving.de/urn:nbn:de:gbv:18-102632 https://ediss.sub.uni-hamburg.de/handle/ediss/8361 BASE Hide details 11 Erfahrung und Gewissheit – Orientierungen in den Wissenschaften und im Alltag. IV. Regensburger Symposium vom 24.-26. März 2011 Thim-Mabrey, Christiane; Brack, Matthias. - : Universitätsbibliothek Regensburg, 2020 BASE Show details 12 ANNIS: A graph-based query system for deeply annotated text corpora ... Krause, Thomas. - : Humboldt-Universität zu Berlin, 2019 BASE Show details 13 Generating Formal Representations of System Specification from Natural Language Requirements Irfan, Zeeshan. - 2019 BASE Show details 14 ANNIS: A graph-based query system for deeply annotated text corpora Krause, Thomas. - : Humboldt-Universität zu Berlin, 2019 BASE Show details 15 Acquiring Architecture Knowledge for Technology Design Decisions ; Erfassung von Architekturwissen für Technologieentwurfsentscheidungen Soliman, Mohamed Aboubakr Mohamed. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2019 BASE Show details 16 Adaptive Approaches to Natural Language Processing in Annotation and Application ; Adaptive Ansätze zur Verarbeitung natürlicher Sprache in Annotation und Anwendung Yimam, Seid Muhie. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2019 BASE Show details 17 Predictive Dependency Parsing ; Vorhersagendes Dependenzparsing Köhn, Arne. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2019 BASE Show details 18 Automatic generation of lexical recognition tests using natural language processing Hamed, Osama Amin. - 2019 BASE Show details 19 Mining and Analyzing User Rationale in Software Engineering ; Gewinnung und Analyse von Nutzerbegründungen in der Softwaretechnik Kurtanović, Zijad. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2018 BASE Show details 20 Operations on Graphs, Arrays and Automata ; Operationen auf Graphen, Arrays und Automaten Paramasivan, Meenakshi. - 2018 BASE Show details Page: 1 2 3 4

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