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| , , en , Electronic Government einführen und entwickeln: Von der Idee zur Praxis, "", 2003 |
| , en , Die Koordinationsplattform in der lernenden Region – Sensibilisierung, Koordination und Qualifizierung, in: "", 2006 |
| , , , , , , , , en , Revealing most suitable CT radiomics features for retrospective studies with heterogeneous datasets, in: European Congress of Radiology (ECR) 2021, ONLINE edition, 2021 |
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, , , , , , , , en , The discriminative power and stability of radiomics features with CT variations: Task-based analysis in an anthropomorphic 3D-printed CT phantom (2021), in: Investigative Radiology, 56:12(820-825)
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| , , , , , , , , , en , Comparing Stability and Discriminatory Power of Handcrafted Versus Deep Radiomics: A 3D-Printed Anthropomorphic Phantom Study, in: 12th IEEE European Workshop on Visual Information Processing, pagina's 62-66, 2024 |
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| , , , , , , en , Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score, in: SPIE Medical Imaging, pagina's 101400O-101400O-9, 2017 |
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| , , , , , , , , en , Assessment of the stability and discriminative power of radiomics features in liver lesions using an anthropomorphic 3D-printed CT phantom, in: Scientific session SGR-SSR, 2021 |
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| , , en , RadLex Terms and Local Texture Features for Multimodal Medical Case Retrieval, in: Multimodal Retrieval in the Medical Domain (MRMD) 2015, Vienna, Austria, Springer, 2015 |
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| , en , Combining Radiology Images and Meta-data for Multimodal Medical Case-Based Retrieval, Springer, 2017 |
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| , , en , Hierarchic Anatomical Structure Segmentation Guided by Spatial Correlations (AnatSeg-Gspac): VISCERAL Anatomy3, in: Proceedings of the VISCERAL Anatomy Grand Challenge at the 2015 IEEE ISBI, pagina's 22-26, CEUR-WS, 2015 |
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, , , , , en , A lung graph model for the radiological assessment of chronic thromboembolic pulmonary hypertension in CT (2020), in: Computers in Biology and Medicine(103962)
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| , , en , Texture classification of anatomical structures in CT using a context-free machine learning approach, in: SPIE Medical Imaging 2015, pagina's 94140W-94140W-14, SPIE, 2015 |
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| , , , en , Overview of the VISCERAL Retrieval Benchmark 2015, in: Multimodal Retrieval in the Medical Domain, Vienna, Austria, Springer, 2015 |
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| , , , en , Epileptogenic lesion quantification in MRI using contralateral 3D texture comparisons, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, pagina's 353-360, Springer Berlin Heidelberg, 2013 |
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| , , , , , , , , , , , , , , , en , VISCERAL - VISual Concept Extraction Challenge in RAdioLogy: ISBI 2014 Challenge Organization, in: Proceedings of the VISCERAL Challenge at ISBI, Beijing, China, pagina's 6-15, 2014 |
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| en , Hierarchical Multi-atlas Based Segmentation for Anatomical Structures: Evaluation in the VISCERAL Anatomy Benchmarks, in: Medical Computer Vision. Large Data in Medical Imaging, Springer, 2014 |
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| en , Multi atlas–based segmentation with data driven refinement, in: Biomedical and Health Informatics (BHI), 2014 IEEE-EMBS International Conference on, Valencia, Spain, pagina's 605-608, IEEE, 2014 |
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| en , Hierarchical multi-structure segmentation guided by anatomical correlations, in: Proceedings of the VISCERAL Challenge at ISBI, Beijing, China, pagina's 32-36, 2014 |
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| , , , en , Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark, hoofdstuk Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark, Springer, 2017 |
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en , Multi-Structure Atlas-Based Segmentation Using Anatomical Regions Of Interest, in: Medical Computer Vision. Large Data in Medical Imaging, Nagoya, Japan, pagina's 217-221, Springer International Publishing, 2014
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| , , , , , , en , Elsevier book on Texture Analysis, hoofdstuk Analysis of Histopathology Images: From Traditional Machine Learning to Deep Learning, 2017 |
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, , en , Deep Multimodal Case-Based Retrieval for Large Histopathology Datasets, in: MICCAI 2017 workshop on Patch-based image analysis, Quebec City, Canada, 2017
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, , , , , , , , , , , , , , , , , , , , , , , , , , en , Cloud–based Evaluation of Organ Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks (2016), in: IEEE Transactions on Medical Imaging
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| , Quantitative analysis of medical images: finding relevant regions-of-interest for medical decision support, University of Geneva, 2017 |
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| , , , en , Responsible Research and Innovation in the Digital Age (2017), in: Communications of the ACM |
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| , "Booster" L'innovation énergétique (2015), in: Valais Valeur ajoutée |
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| , L'Energy Living Lab, un écosystème d'innovation pour la transition énergétique, Journée internationale de la sociologie de l'énergie, Tours, 2015 |
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| , L'Energy Living Lab pour booster l'innovation énergétique (2015), in: UVAM Tribune(p.47) |
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| , L'usager au centre de la réflexion (2015), in: Bulletin electrosuisse/VSE/AES |
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| , BusiNETvs: Développement durable, Banque Cantonale du Valais, HES-SO Valais, 2011 |
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| , , , , en , Energy management in a public building: A case study co-designing the building energy management system, 2017 |
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| , en , L’Energy Living Lab : un écosystème d’innovation pour favoriser la co-création de services énergétiques, Association française du Marketing, Marrakesh, 2015 |
| , en , How to keep a living lab alive (2015), in: Journal INFO |
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| , en , How to keep a living lab alive, European Network of Living Labs, Amsterdam, 2014 |
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| , en , Investigating transnational philanthropy in hospitality industry, 5th International tourism congress, The image and sustainability of tourist destination, 2011 |
| , en , Investigating the added value of a guest donation program (hotels that help) in hospitality enterprises, Advances in hospitality and tourism marketing and management, conference proceedings, 2011 |
| , , , , , , , , , , , , , , , , , , , , en , Overview of LifeCLEF 2023: evaluation of AI models for the identification and prediction of birds, plants, snakes and fungi, in: CLEF 2023 proceedings, Thessaloniki, Greece, 2023 |
| , , , , , , , en , Biodiversity information retrieval through content-based identification: a long-term evaluation, Springer, 2019 |
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| , , , , , , , en , Are species identification tools biodiversity-friendly, in: ACM Multimedia Workshop on Multimedia Analysis of Ecological Data, Barcelona, Spain, 2014 |
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| , , , , , , , en , Are multimedia identification tools biodiversity-friendly, in: ACM Multimedia Workshop on Multimedia Analysis of Ecological Data, Barcelona, Spain, 2013 |
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| , , , , , , en , Overview of LifeCLEF 2018: a large-scale evaluation of species identification and recommendation algorithms in the era of AI, in: CLEF conference proceeding, Avignon, France, Springer, 2018 |
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| , , , , , , , en , LifeCLEF 2019: Biodiversity Identification and Prediction Challenges, in: ECIR 2019, Cologne, Germany, 2019 |
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| , , , , , , , , , en , Overview of LifeCLEF 2019: a new snapshot of the performance of species identification and prediction algorithms, in: CLEF conference Proceedings, Lugano, Switzerland, Springer LNCS, 2019 |
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| , , , , en , Implicit biodiversity monitoring from mobile search logs (2016), in: ACM Multimedia |
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| , , , , , , , , en , LifeCLEF 2016: Multimedia Life Species Identication Challenges, in: CLEF Proceedings, Springer, 2016 |
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, , , , , , , , en , LifeCLEF 2017 Lab Overview: multimedia species identification challenges, in: CLEF 2017 Proceedings, 2017
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| , , , , , , , , , , , , , , en , LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges, in: ECIR 2020, Lisbon, Portugal, Springer LNCS, 2020 |
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| , , , , , , , , , , , , , , , , en , Overview of LifeCLEF 2020: a System-oriented Evaluation of Automated Species Identification and Species Distribution Prediction, Thessaloniki, Greece, Springer LNCS, 2020 |
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| , , , , , , , en , LifeCLEF 2022 Teaser: an evaluation ofMachine-Learning based Species Identification and Species Distribution Prediction, in: ECIR 2022, Stavanger, Norway, 2022 |
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| , , , , , en , LifeCLEF 2023 teaser: Species Identification and Prediction Challenges, in: ECIR 2023, Dublin, Ireland, 2023 |
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