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description Publicationkeyboard_double_arrow_right Article 2019 GermanyPublisher:Elsevier BV Funded by:EC | IMAGINEEC| IMAGINETimo Lüddecke; Alejandro Agostini; Michael Fauth; Minija Tamosiunaite; Florentin Wörgötter;The distributional hypothesis states that the meaning of a concept is defined through the contexts it occurs in. In practice, often word co-occurrence and proximity are analyzed in text corpora for a given word to obtain a real-valued semantic word vector, which is taken to (at least partially) encode the meaning of this word. Here we transfer this idea from text to images, where pre-assigned labels of other objects or activations of convolutional neural networks serve as context. We propose a simple algorithm that extracts and processes object contexts from an image database and yields semantic vectors for objects. We show empirically that these representations exhibit on par performance with state-of-the-art distributional models over a set of conventional objects. For this we employ well-known word benchmarks in addition to a newly proposed object-centric benchmark. peerReviewed
Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.artint.2018.12.009&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.artint.2018.12.009&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 GermanyPublisher:SAGE Publications Funded by:EC | ReconCellEC| ReconCellAuthors: Mohamad Javad Aein; Eren Erdal Aksoy; Florentin Wörgötter;Mohamad Javad Aein; Eren Erdal Aksoy; Florentin Wörgötter;When a robot has to imitate an observed action sequence, it must first understand the inherent characteristic features of the individual actions. Such features need to reflect the semantics of the action with a high degree of invariance between different demonstrations of the same action. At the same time the machine needs to be able to execute the action sequence in any appropriate situation. In this study, we introduce a new library of actions, which is a generic framework for executing manipulation actions on robotic systems by combining features that capture action semantics with a framework for execution. We focus on manipulation actions and first create a generic representation consisting of symbolic and sub-symbolic components. To link these two domains we introduce a finite state machine allowing for sequential execution with error handling. The framework is developed from observing humans which provides us with a high degree of grounding. To quantitatively evaluate the scalability of the proposed approach, we conducted a large set of experiments involving different actions performed either individually or sequentially with various types of objects in different scene contexts. Research Executive Agency https://doi.org/10.13039/501100000783
Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedThe International Journal of Robotics ResearchArticle . 2019 . Peer-reviewedLicense: SAGE TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/0278364919850295&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedThe International Journal of Robotics ResearchArticle . 2019 . Peer-reviewedLicense: SAGE TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/0278364919850295&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
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description Publicationkeyboard_double_arrow_right Article 2019 GermanyPublisher:Elsevier BV Funded by:EC | IMAGINEEC| IMAGINETimo Lüddecke; Alejandro Agostini; Michael Fauth; Minija Tamosiunaite; Florentin Wörgötter;The distributional hypothesis states that the meaning of a concept is defined through the contexts it occurs in. In practice, often word co-occurrence and proximity are analyzed in text corpora for a given word to obtain a real-valued semantic word vector, which is taken to (at least partially) encode the meaning of this word. Here we transfer this idea from text to images, where pre-assigned labels of other objects or activations of convolutional neural networks serve as context. We propose a simple algorithm that extracts and processes object contexts from an image database and yields semantic vectors for objects. We show empirically that these representations exhibit on par performance with state-of-the-art distributional models over a set of conventional objects. For this we employ well-known word benchmarks in addition to a newly proposed object-centric benchmark. peerReviewed
Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.artint.2018.12.009&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.artint.2018.12.009&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 GermanyPublisher:SAGE Publications Funded by:EC | ReconCellEC| ReconCellAuthors: Mohamad Javad Aein; Eren Erdal Aksoy; Florentin Wörgötter;Mohamad Javad Aein; Eren Erdal Aksoy; Florentin Wörgötter;When a robot has to imitate an observed action sequence, it must first understand the inherent characteristic features of the individual actions. Such features need to reflect the semantics of the action with a high degree of invariance between different demonstrations of the same action. At the same time the machine needs to be able to execute the action sequence in any appropriate situation. In this study, we introduce a new library of actions, which is a generic framework for executing manipulation actions on robotic systems by combining features that capture action semantics with a framework for execution. We focus on manipulation actions and first create a generic representation consisting of symbolic and sub-symbolic components. To link these two domains we introduce a finite state machine allowing for sequential execution with error handling. The framework is developed from observing humans which provides us with a high degree of grounding. To quantitatively evaluate the scalability of the proposed approach, we conducted a large set of experiments involving different actions performed either individually or sequentially with various types of objects in different scene contexts. Research Executive Agency https://doi.org/10.13039/501100000783
Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedThe International Journal of Robotics ResearchArticle . 2019 . Peer-reviewedLicense: SAGE TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/0278364919850295&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Göttingen Research O... arrow_drop_down Göttingen Research Online PublicationsArticle . 2019Data sources: Göttingen Research Online PublicationsPublikationenserver der Georg-August-Universität GöttingenArticle . 2019 . Peer-reviewedThe International Journal of Robotics ResearchArticle . 2019 . Peer-reviewedLicense: SAGE TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/0278364919850295&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu