Results 21 to 30 of about 287,772 (335)

Attention-Based Neural Text Segmentation [PDF]

, 2018
Text segmentation plays an important role in various Natural Language Processing (NLP) tasks like summarization, context understanding, document indexing and document noise removal. Previous methods for this task require manual feature engineering, huge memory requirements and large execution times. To the best of our knowledge, this paper is the first
Badjatiya, Pinkesh, Kurisinkel, Litton J, Gupta, Manish, Varma, Vasudeva   +3 more
openaire   +2 more sources

Design and analysis of a lean interface for Sanskrit corpus annotation

Journal of Language Modelling, 2016
We describe an innovative computer interface designed to assist annotators in the efficient selection of segmentation solutions for proper tagging of Sanskrit corpora.
Pawan Goyal, Gerard Huet
doaj   +1 more source

Text segmentation of health examination item based on character statistics and information measurement

CAAI Transactions on Intelligence Technology, 2018
This study explores the segmentation algorithm of item text data, especially of single long length data in health examination. In the specific implementation, a large amount of historical health examination data is analysed. Using the method of character
Hui An, Dahui Wang, Zhigeng Pan, Meiling Chen, Xinting Wang   +4 more
doaj   +1 more source

Segmentation and Recognition for Historical Tibetan Document Images

IEEE Access, 2020
As a shining pearl in traditional Tibetan culture, historical Tibetan documents have received extensive attention from historians, linguists and Buddhist scholars.
Longlong Ma, Congjun Long, Lijuan Duan, Xiqun Zhang, Yanxing Li, Quanchao Zhao   +5 more
doaj   +1 more source

TV News Story Segmentation Based on Semantic Coherence and Content Similarity [PDF]

, 2010
In this paper, we introduce and evaluate two novel approaches, one using video stream and the other using close-caption text stream, for segmenting TV news into stories.
Goyal, A., Hopfgartner, F., Jose, J., Misra, H., Punitha, P.   +4 more
core   +1 more source

Adaptive text mining: Inferring structure from sequences [PDF]

, 2004
Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes.
Witten, Ian H.
core   +2 more sources

Text-Guided Image Manipulation via Generative Adversarial Network With Referring Image Segmentation-Based Guidance

IEEE Access, 2023
This study proposes a novel text-guided image manipulation method that introduces referring image segmentation into a generative adversarial network. The proposed text-guided image manipulation method aims to manipulate images containing multiple objects
Yuto Watanabe, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama   +4 more
doaj   +1 more source

Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays [PDF]

, 2015
BACKGROUND: Tissue microarrays (TMAs) have become a valuable resource for biomarker expression in translational research. Immunohistochemical (IHC) assessment of TMAs is the principal method for analysing large numbers of patient samples, but manual IHC ...
A Madabhushi, AE Rizzardi, Alastair M Thompson, AS Coates, Colin A Purdie, DC Allred, GK Rohde, J Cohen, K Arihiro, Lee B Jordan, M Dowsett, M Ilyas, M Veta, MN Gurcan, R Yerushalmi, S Detre, S Fasanella, Shazia Akbar, Stephen J McKenna, W Jonat, ZM Mohammed   +20 more
core   +3 more sources

Shot boundary detection in MPEG videos using local and global indicators [PDF]

, 2009
Shot boundary detection (SBD) plays important roles in many video applications. In this letter, we describe a novel method on SBD operating directly in the compressed domain.
Chen, J., Jiang, J., Ren, Jinchang
core   +1 more source

LLM-Enhanced Semantic Text Segmentation

Applied Sciences
This study investigates semantic text segmentation enhanced by large language model (LLM) embeddings. We assess how effectively embeddings capture semantic coherence and topic closure by integrating them into both classical clustering algorithms and a ...
Alexander Krassovitskiy, Rustam Mussabayev, Kirill Yakunin   +2 more
doaj   +1 more source