Ekta Vats
Associate senior lecturer/Assistant Professor at Department of Information Technology; Division of Systems and Control
- Telephone:
- +46 18 471 34 40
- E-mail:
- ekta.vats@it.uu.se
- Visiting address:
- Hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
- Academic merits:
- Docent
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Short presentation
I am an Assistant Professor in Machine Learning, Docent in Computerised Image Processing, and a Beijer Researcher at The Beijer Laboratory for Artificial Intelligence Research. I lead the Uppsala Vision, Language and Learning group and our research mission is to build fundamental AI/ML methods for computer vision and language modeling to address societal challenges.
Keywords
- artifical intelligence
- computer vision
- data science
- deep learning
- digital humanities
- ethical ai
- handwritten text recognition
- human action recognition
- image analysis
- language modeling
- large language models (llm)
- machine learning
- natural language processing
- ocr
Research
Our research is highly interdisciplinary and collaborative, and spans topics such as Large Language Models in Computer Vision and NLP, text/image/video classification, text recognition (OCR, Handwritten), multispectral imaging, and NLP tasks (sentiment analysis, Named entity recognition).
Research group: Uppsala Vision, Language and Learning
Media
Beijer Research Group Profile
Get an understanding of my ongoing research in the lab in the video
Beijer Researcher at the Beijer Foundation
How AI and machine learning can help address societal challenges?
https://www.beijerstiftelsen.se/en/component/zoo/researchers/ekta-vats-en?Itemid=234
Publications
Selection of publications
- Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition (2024)
- Paired Image to Image Translation for Strikethrough Removal from Handwritten Words (2022)
- AttentionHTR (2022)
- Strikethrough Removal from Handwritten Words Using CycleGANs (2021)
- Training-Free and Segmentation-Free Word Spotting using Feature Matching and Query Expansion (2019)
- Learning surrogate models of document image quality metrics for automated document image processing (2018)
- On-the-fly historical handwritten text annotation (2017)
- Automatic document image binarization using Bayesian optimization (2017)
Recent publications
- Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition (2024)
- Automatic classification of historical texts using a BERT model (2023)
- Paired Image to Image Translation for Strikethrough Removal from Handwritten Words (2022)
- AttentionHTR (2022)
- Word Recognition using Embedded Prototype Subspace Classifiers on a new Imbalanced Dataset (2021)
All publications
Articles
- Word Recognition using Embedded Prototype Subspace Classifiers on a new Imbalanced Dataset (2021)
- The Significance of Script Proportions in the Medieval Swedish Script (2021)
- In search of the scribe (2019)
- Radial line Fourier descriptor for historical handwritten text representation (2018)
Conferences
- Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition (2024)
- Automatic classification of historical texts using a BERT model (2023)
- Paired Image to Image Translation for Strikethrough Removal from Handwritten Words (2022)
- AttentionHTR (2022)
- Strikethrough Removal from Handwritten Words Using CycleGANs (2021)
- Making large collections of handwritten material easily accessible and searchable (2019)
- Subspace Learning and Classification (2019)
- Embedded Prototype Subspace Classification (2019)
- Creating an Atlas over Handwritten Script Signs (2019)
- Training-Free and Segmentation-Free Word Spotting using Feature Matching and Query Expansion (2019)
- TexT – Text extractor tool for handwritten document transcription and annotation (2018)
- Radial line Fourier descriptor for historical handwritten text representation (2018)
- An intelligent user interface for efficient semi-automatic transcription of historical handwritten documents (2018)
- Exploring the Applicability of Capsule Networks for WordSpotting in Historical Handwritten Manuscripts (2018)
- Word Spotting in Historical Handwritten Manuscripts using Capsule Networks (2018)
- Learning surrogate models of document image quality metrics for automated document image processing (2018)
- Extracting script features from a large corpus of handwritten documents (2018)
- On-the-fly historical handwritten text annotation (2017)
- Automatic document image binarization using Bayesian optimization (2017)