Results 11 to 20 of about 7,392 (64)

Abstractive Text Summarization in Arabic-Like Script Using Multi-Encoder Architecture and Semantic Extraction Techniques

IEEE Access
In the field of Natural Language Processing (NLP), the task of text summarization plays a vital role in understanding textual content and producing concise summaries.
Wajiha Fatima, Syed Saqib Raza Rizvi, Taher M. Ghazal, Qasem M. Kharma, Munir Ahmad, Sagheer Abbas, M. Furqan, K. M. Adnan   +7 more
semanticscholar   +1 more source

Evaluating ChatGPT-4 and Machine Learning Models for Sentiment Analysis on a Multi-Script Moroccan Arabic Corpus: Insights, Challenges, and Future Directions

Journal of Data Mining & Digital Humanities
The application of Large Language Models (LLMs) to low-resource languages and dialects, such as Moroccan Arabic (MA), remains a relatively unexplored area.
Mohamed HANNANI, Abdelhadi SOUDI, Kristof Van Laerhoven   +2 more
semanticscholar   +1 more source

Before it's too late: The extinction script, multi‐species reproductive futurism and Extinction Rebellion

Transactions (Institute of British Geographers)
Whether it's a speech from a politician, a warning in a scientific article, or activists chanting in the street, the climate crisis is made and remade through competing claims about the future.
Amy Robson
semanticscholar   +1 more source

Bag-of-visual-words for signature-based multi-script document retrieval [PDF]

Neural computing & applications (Print), 2018
An end-to-end architecture for multi-script document retrieval using handwritten signatures is proposed in this paper. The user supplies a query signature sample, and the system exclusively returns a set of documents that contain the query signature.
Ranju Mandal, P. Roy, U. Pal, M. Blumenstein   +3 more
semanticscholar   +1 more source

Artistic multi-script identification at character level with extreme learning machine

, 2020
In this work, a novel problem, namely artistic multi-script identification at character level has been addressed. Two types of documents: real/ natural and synthetic have been used for dataset preparation.
Dr. Mridul Ghosh, H. Mukherjee, S. Obaidullah, K. Santosh, N. Das, K. Roy   +5 more
semanticscholar   +1 more source

MuSIC: A Novel Multi-Scale Deep Neural Framework for Script Identification in the Wild

IEEE Access
Script identification in digital images is crucial for automated text reading in multilingual contexts. Developing a robust script-identifier in complex environments is challenging due to prevalence of mobiles and digitized documents. This paper presents
Tauseef Khan, M. Saif, A. Mollah
semanticscholar   +1 more source

Word searching in scene image and video frame in multi-script scenario using dynamic shape coding [PDF]

Multimedia tools and applications, 2017
Retrieval of text information from natural scene images and video frames is a challenging task due to its inherent problems like complex character shapes, low resolution, background noise, etc.
P. Roy, A. Bhunia, Avirup Bhattacharyya, U. Pal   +3 more
semanticscholar   +1 more source

Multi-script morphological transducers and transcribers for seven Turkic languages

, 2020
This paper describes ongoing work to augment morphological transducers for seven Turkic languages with support for multiple scripts each, as well as preliminary work adding IPA transcription systems.
Jonathan North Washington, Francis M. Tyers, O. Kuyrukçu   +2 more
semanticscholar   +1 more source

A Hybrid Approach for Skew Detection and Correction in the Multi-script Scanned Document

Asian Journal of Research in Computer Science, 2019
Skew detection and correction of a scanned document is a very important step in Optical Character Recognition because skew of scanned document is reducing the accuracy of text line approach for skew detection and correction to calculate the skew angle on
M. Ramanan
semanticscholar   +1 more source

Multi-script text versus non-text classification of regions in scene images

Journal of Visual Communication and Image Representation, 2019
Text versus non-text region classification is an essential but difficult step in scene-image analysis due to the considerable shape complexity of text and background patterns.
Bowornrat Sriman, Lambert Schomaker
semanticscholar   +1 more source