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Hast, AndersORCID iD iconorcid.org/0000-0003-1054-2754
Publications (10 of 53) Show all publications
Hast, A., Mårtensson, L., Vats, E. & Heil, R. (2019). Creating an Atlas over Handwritten Script Signs. In: Digital Humanities in the Nordic Countries: . Paper presented at DHN 2019, March 6–8, Copenhagen, Denmark.
Open this publication in new window or tab >>Creating an Atlas over Handwritten Script Signs
2019 (English)In: Digital Humanities in the Nordic Countries, 2019Conference paper, Poster (with or without abstract) (Refereed)
National Category
Computer Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-373517 (URN)
Conference
DHN 2019, March 6–8, Copenhagen, Denmark
Available from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-01-17
Hast, A., Lind, M. & Vats, E. (2019). Embedded Prototype Subspace Classification: A subspace learning framework. In: Computer Analysis of Images and Patterns: . Paper presented at CAIP 2019, September 2–6, Salerno, Italy. Springer
Open this publication in new window or tab >>Embedded Prototype Subspace Classification: A subspace learning framework
2019 (English)In: Computer Analysis of Images and Patterns, Springer, 2019Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Springer, 2019
Series
Lecture Notes in Computer Science
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:uu:diva-389452 (URN)
Conference
CAIP 2019, September 2–6, Salerno, Italy
Available from: 2019-07-14 Created: 2019-07-14 Last updated: 2019-07-22
Mårtensson, L., Vats, E., Hast, A. & Fornés, A. (2019). In search of the scribe: Letter spotting as a tool for identifying scribes in large handwritten text corpora. Human IT, 14(2), 95-120
Open this publication in new window or tab >>In search of the scribe: Letter spotting as a tool for identifying scribes in large handwritten text corpora
2019 (English)In: Human IT, ISSN 1402-1501, E-ISSN 1402-151X, Vol. 14, no 2, p. 95-120Article in journal (Refereed) Published
National Category
Computer Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-373929 (URN)
Available from: 2019-01-17 Created: 2019-01-17 Last updated: 2019-01-17Bibliographically approved
Hast, A., Cullhed, P., Vats, E. & Abrate, M. (2019). Making large collections of handwritten material easily accessible and searchable. In: Digital Libraries: Supporting Open Science. Paper presented at IRCDL 2019, January 31 – February 1, Pisa, Italy (pp. 18-28). Springer
Open this publication in new window or tab >>Making large collections of handwritten material easily accessible and searchable
2019 (English)In: Digital Libraries: Supporting Open Science, Springer, 2019, p. 18-28Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer, 2019
Series
Communications in Computer and Information Science ; 988
National Category
Computer and Information Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-373515 (URN)10.1007/978-3-030-11226-4_2 (DOI)978-3-030-11225-7 (ISBN)
Conference
IRCDL 2019, January 31 – February 1, Pisa, Italy
Available from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-01-17Bibliographically approved
Hast, A., Lind, M. & Vats, E. (2019). Subspace Learning and Classification. In: Proc. 3rd Swedish Symposium on Deep Learning: . Paper presented at SSDL 2019, June 10–11, Norrköping, Sweden.
Open this publication in new window or tab >>Subspace Learning and Classification
2019 (English)In: Proc. 3rd Swedish Symposium on Deep Learning, 2019Conference paper, Poster (with or without abstract) (Other academic)
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:uu:diva-389451 (URN)
Conference
SSDL 2019, June 10–11, Norrköping, Sweden
Available from: 2019-07-14 Created: 2019-07-14 Last updated: 2019-07-22
Vats, E., Hast, A. & Fornés, A. (2019). Training-Free and Segmentation-Free Word Spotting using Feature Matching and Query Expansion. In: Proc. 15th International Conference on Document Analysis and Recognition: . Paper presented at ICDAR 2019, September 20–25, Sydney, Australia.
Open this publication in new window or tab >>Training-Free and Segmentation-Free Word Spotting using Feature Matching and Query Expansion
2019 (English)In: Proc. 15th International Conference on Document Analysis and Recognition, 2019Conference paper, Oral presentation with published abstract (Refereed)
National Category
Computer Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-389453 (URN)
Conference
ICDAR 2019, September 20–25, Sydney, Australia
Available from: 2019-07-14 Created: 2019-07-14 Last updated: 2019-07-22
Hast, A., Sablina, V. A., Sintorn, I.-M. & Kylberg, G. (2018). A fast Fourier based feature descriptor and a cascade nearest neighbour search with an efficient matching pipeline for mosaicing of microscopy images. Pattern Recognition and Image Analysis, 28(2), 261-272
Open this publication in new window or tab >>A fast Fourier based feature descriptor and a cascade nearest neighbour search with an efficient matching pipeline for mosaicing of microscopy images
2018 (English)In: Pattern Recognition and Image Analysis, ISSN 1054-6618, Vol. 28, no 2, p. 261-272Article in journal (Refereed) Published
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-354147 (URN)10.1134/S1054661818020050 (DOI)
Available from: 2018-06-16 Created: 2018-06-19 Last updated: 2018-06-20Bibliographically approved
Hast, A. & Vats, E. (2018). An intelligent user interface for efficient semi-automatic transcription of historical handwritten documents. In: Proc. 23rd International Conference on Intelligent User Interfaces Companion: . Paper presented at IUI 2018, March 7–11, Tokyo, Japan. New York: ACM Press, Article ID 48.
Open this publication in new window or tab >>An intelligent user interface for efficient semi-automatic transcription of historical handwritten documents
2018 (English)In: Proc. 23rd International Conference on Intelligent User Interfaces Companion, New York: ACM Press, 2018, article id 48Conference paper, Published paper (Refereed)
Abstract [en]

Transcription of large-scale historical handwritten document images is a tedious task. Machine learning techniques, such as deep learning, are popularly used for quick transcription, but often require a substantial amount of pre-transcribed word examples for training. Instead of line-by-line word transcription, this paper proposes a simple training-free gamification strategy where all occurrences of each arbitrarily selected word is transcribed once, using an intelligent user interface implemented in this work. The proposed approach offers a fast and user-friendly semi-automatic transcription that allows multiple users to work on the same document collection simultaneously.
Place, publisher, year, edition, pages
New York: ACM Press, 2018
National Category
Computer and Information Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-345637 (URN)10.1145/3180308.3180357 (DOI)000458680100048 ()978-1-4503-5571-1 (ISBN)
Conference
IUI 2018, March 7–11, Tokyo, Japan
Projects
eSSENCE
Funder
Riksbankens Jubileumsfond, NHS14-2068:1eSSENCE - An eScience Collaboration
Available from: 2018-03-05 Created: 2018-03-12 Last updated: 2019-03-11Bibliographically approved
Heil, R., Vats, E. & Hast, A. (2018). Exploring the Applicability of Capsule Networks for WordSpotting in Historical Handwritten Manuscripts. In: : . Paper presented at Swedish Symposium on Deep Learning 2018.
Open this publication in new window or tab >>Exploring the Applicability of Capsule Networks for WordSpotting in Historical Handwritten Manuscripts
2018 (English)Conference paper, Oral presentation only (Other academic)
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-373512 (URN)
Conference
Swedish Symposium on Deep Learning 2018
Available from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-01-17
Vats, E., Hast, A. & Mårtensson, L. (2018). Extracting script features from a large corpus of handwritten documents. In: Digital Humanities in the Nordic Countries: Book of Abstracts. Paper presented at DHN 2018, March 7–9, Helsinki, Finland.
Open this publication in new window or tab >>Extracting script features from a large corpus of handwritten documents
2018 (English)In: Digital Humanities in the Nordic Countries: Book of Abstracts, 2018Conference paper, Oral presentation with published abstract (Refereed)
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-356773 (URN)
Conference
DHN 2018, March 7–9, Helsinki, Finland
Available from: 2018-08-06 Created: 2018-08-06 Last updated: 2018-11-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1054-2754

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