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Auteur Peter Kiefer |
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Spatial big data and machine learning in GIScience, Workshop at GIScience 2018, Melbourne, Australia, 28 August 2018 / Martin Raubal (2018)
Titre : Spatial big data and machine learning in GIScience, Workshop at GIScience 2018, Melbourne, Australia, 28 August 2018 : Proceedings Type de document : Actes de congrès Auteurs : Martin Raubal, Éditeur scientifique ; Shaowen Wang, Éditeur scientifique ; Mengyu Guo, Éditeur scientifique ; David Jonietz, Éditeur scientifique ; Peter Kiefer, Éditeur scientifique Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2018 Conférence : Workshop 2018 on Spatial big data and machine learning 28/08/2018 28/08/2018 Melbourne Australie OA Proceedings Importance : 53 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] apprentissage automatique
[Termes IGN] données localisées
[Termes IGN] données massives
[Termes IGN] interface homme-machine
[Termes IGN] trajectoire (véhicule non spatial)Note de contenu : PART 1: TRAJECTORIES
- Stay-Move Tree for Summarizing Spatiotemporal Trajectories / Eun-Kyeong Kim
- Detection of Unsigned Ephemeral Road Incidents by Visual Cues / Alex Levering, Kourosh Khoshelham, Devis Tuia, and Martin Tomko
- Convolutional Neural Network for Traffic Signal Inference based on GPS Traces / Y. Méneroux, V. Dizier, M. Margollé, M.D. Van Damme, H.Kanasugi, A. Le Guilcher, G. Saint Pierre, and Y. Kato
- Using Stream Processing to Find Suitable Rides: An Exploration based on New York City Taxi Data / Roswita Tschümperlin, Dominik Bucher, and Joram Schito
- Classification of regional dominant movement patterns in trajectories with a convolutional neural
network / Can Yang and Gyozo Gidófalvi
PART 2: COGNITION & HCI
- Spatial Big Data for Human-Computer Interaction / Ioannis Giannopoulos
- Unsupervised Clustering of Eye Tracking Data / Fabian Göbel and Henry Martin
- Collections of Points of Interest: How to Name Them and Why it Matters / Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao, Rui Zhu, Bo Yan, Grant McKenzie, Anagha Uppal, and Blake Regalia
PART 3: SPATIAL PATTERNS
- A Multi-scale Spatio-temporal Approach to Analysing the changing inequality in the Housing Market during 2001-2014 / Yingyu Feng and Kelvyn Jones
- Automated social media content analysis from urban green areas – Case Helsinki / Vuokko Heikinheimo, Henrikki Tenkanen, Tuomo Hiippala, Olle Järv, and Tuuli Toivonen
- Long short-term memory networks for county-level corn yield estimation / Haifeng Li, Yudi Wang, Renhai Zhong, Hao Jiang, and Tao Lin
- Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering / Torben Peters and Claus BrennerNuméro de notice : 17546 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes En ligne : http://spatialbigdata.ethz.ch/index.php/proceedings/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91338 ContientDocuments numériques
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Spatial big data and machine learning in GIScience 2018 - pdf éditeurAdobe Acrobat PDF Controllability matters : The user experience of adaptive maps / Peter Kiefer in Geoinformatica, vol 21 n° 3 (July - September 2017)
[article]
Titre : Controllability matters : The user experience of adaptive maps Type de document : Article/Communication Auteurs : Peter Kiefer, Auteur ; Ioannis Giannopoulos, Auteur ; Vasileios Athanasios Anagnostopoulos, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 619 - 641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartologie
[Termes IGN] interface graphique
[Termes IGN] lecture de carte
[Termes IGN] utilisateur civil
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Adaptive map interfaces have the potential of increasing usability by providing more task dependent and personalized support. It is unclear, however, how map adaptation must be designed to avoid a loss of control, transparency, and predictability. This article investigates the user experience of adaptive map interfaces in the context of gaze-based activity recognition. In a Wizard of Oz experiment we study two adaptive map interfaces differing in the degree of controllability and compare them to a non-adaptive map interface. Adaptive interfaces were found to cause higher user experience and lower perceived cognitive workload than the non-adaptive interface. Among the adaptive interfaces, users clearly preferred the condition with higher controllability. Results from structured interviews reveal that participants dislike being interrupted in their spatial cognitive processes by a sudden adaptation of the map content. Our results suggest that adaptive map interfaces should provide their users with control at what time an adaptation will be performed. Numéro de notice : A2017-384 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0282-x En ligne : https://doi.org/10.1007/s10707-016-0282-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85817
in Geoinformatica > vol 21 n° 3 (July - September 2017) . - pp 619 - 641[article]Where am I? Investigating map matching during self-localization with mobile eye tracking in an urban environment / Peter Kiefer in Transactions in GIS, vol 18 n° 5 (October 2014)
[article]
Titre : Where am I? Investigating map matching during self-localization with mobile eye tracking in an urban environment Type de document : Article/Communication Auteurs : Peter Kiefer, Auteur ; Ioannis Giannopoulos, Auteur ; Martin Raubal, Auteur Année de publication : 2014 Article en page(s) : pp 660 – 686 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] géolocalisation
[Termes IGN] géopositionnement
[Termes IGN] sémiologie graphique
[Termes IGN] signe conventionnelRésumé : (Auteur) Self-localization is the process of identifying one's current position on a map, and it is a crucial part of any wayfinding process. During self-localization the wayfinder matches visually perceptible features of the environment, such as landmarks, with map symbols to constrain potential locations on the map. The success of this visual matching process constitutes an important factor for the success of self-localization. In this research we aim at observing the visual matching process between environment and map during self-localization with real-world mobile eye tracking. We report on one orientation and one self-localization experiment, both in an outdoor urban environment. The gaze data collected during the experiments show that successful participants put significantly more visual attention to those symbols on the map that were helpful in the given situation than unsuccessful participants. A sequence analysis revealed that they also had significantly more switches of visual attention between map symbols and their corresponding landmarks in the environment, which suggests they were following a more effective self-localization strategy. Numéro de notice : A2014-509 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12067 Date de publication en ligne : 27/10/2013 En ligne : https://doi.org/10.1111/tgis.12067 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74108
in Transactions in GIS > vol 18 n° 5 (October 2014) . - pp 660 – 686[article]