Export 29 results:
Filters: Author is Thomas de Lange [Clear All Filters]
Kvasir-SEG: A Segmented Polyp Dataset In MMM2020. Daejeon, Korea: MMM 2020 26TH INTERNATIONAL CONFERENCE ON MULTIMEDIA MODELING, 2020.
Deep Learning for Automatic Generation of Endoscopy Reports." Gastrointestinal Endoscopy 89, no. 6 (2019)."
Efficient Processing of Medical Videos in a Multi-auditory Environment Using Gpu Lending. NVIDIA's GPU Technology Conference (GTC), 2019.
Kunstig intelligens for endoskopi – Automatisk deteksjon av lesjoner i sanntid. NGF Nytt, Vol. 26, No 1, March 2019, p. 34: Norsk Gastroenterologisk Forening, 2019.
Maskinlæringssystemer for gastrointestinale endoskopier." Best Practice Nordic - Gastroenterologi (2019)."
ResUNet++: An Advanced Architecture for Medical Image Segmentation In 2019 IEEE International Symposium on Multimedia (ISM). San Diego, California, USA: IEEE, 2019.
Automatic Detection of Angiectasia: Evaluation of Deep Learning and Handcrafted Approaches In IEEE Conference on Biomedical and Health Informatics (BHI) 2018., 2018.
Comprehensible Reasoning and Automated Reporting of Medical Examinations Based on Deep Learning Analysis In Proceedings of the 9th ACM Multimedia Systems Conference. Amsterdam, Netherlands: ACM, 2018.
Deep Learning and Handcrafted Feature Based Approaches for Automatic Detection of Angiectasia In 2018 IEEE Conference on Biomedical and Health Informatics (BHI). IEEE, 2018.
Deep Learning and Hand-crafted Feature Based Approaches for Polyp Detection in Medical Videos In 31st IEEE CBMS International Symposium on Computer-Based Medical Systems. Karlstad, Sweden: IEEE, 2018.
Dissecting Deep Neural Networks for Better Medical Image Classification and Classification Understanding In 31st IEEE CBMS International Symposium on Computer-Based Medical Systems. Karlstad, Sweden: IEEE, 2018.
Medico Multimedia Task at MediaEval 2018 In Working Notes Proceedings of the MediaEval 2018 Workshop. CEUR Workshop Proceedings, 2018.
Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy." World Journal of Gastroenterology 45, no. 24 (2018): 5057-5062."
Mimir: An Automatic Reporting and Reasoning System for Deep Learning based Analysis in the Medical Domain In Proceedings of the 9th ACM Multimedia Systems Conference. Amsterdam, Netherlands: ACM, 2018.
Tradeoffs using Binary and Multiclass Neural Network Classification for Medical Multidisease Detection In 2018 IEEE International Symposium on Multimedia (ISM). IEEE, 2018.
A comparison of deep learning with global features for gastrointestinal disease detection In MediaEval Benchmark 2017, Edited by M. Riegler. Dublin, Ireland: CEUR-WS.org, 2017.
Efficient disease detection in gastrointestinal videos – global features versus neural networks." Multimedia Tools and Applications 76, no. 21 (2017): 22493-22525."
EIR: changing the scene of automatic detection software for gastrointestinal endoscopy In World Congress of GI Endoscopy, Edited by T. de Lange. Hyderabad, India: World Endoscopic Organisation, 2017.
From Annotation to Computer-Aided Diagnosis: Detailed Evaluation of a Medical Multimedia System." ACM Transactions on Multimedia Computing, Communications, and Applications 13, no. 3 (2017)."
A Holistic Multimedia System for Gastrointestinal Tract Disease Detection In 8th annual ACM conference on Multimedia Systems (MMSys), Edited by P. Cesar and C. Hsu. ACM, 2017.
Kvasir: A Multi-Class Image-Dataset for Computer Aided Gastrointestinal Disease Detection In ACM Multimedia Systems. Taiwan: ACM, 2017.
Multimedia for medicine: the medico Task at mediaEval 2017 In MediaEval Benchmark 2017, Edited by M. Riegler. Dublin, Ireland: CEUR-WS.org, 2017.
Nerthus: A Bowel Preparation Quality Video Dataset In ACM Multimedia Systems. Taipei: ACM, 2017.
Computer Aided Disease Detection System for Gastrointestinal Examinations In Multimedia Systems Conference 2016. New York: ACM, 2016.
Efficient Processing of Videos in a Multi Auditory Environment Using Device Lending of GPUs In The 7th International Conference on Multimedia Systems (MMSys). ACM, 2016.