Muutke küpsiste eelistusi

E-raamat: Document Analysis and Recognition - ICDAR 2023 Workshops: San Jose, CA, USA, August 24-26, 2023, Proceedings, Part II

Edited by , Edited by
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 74,09 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Document Analysis and Recognition - ICDAR 2023 Workshops: San Jose, CA, USA, August 24-26, 2023, Proceedings, Part IISuurem pilt
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This two-volume set LNCS 14193-14194 constitutes the proceedings of International Workshops co-located with the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, held in San José, CA, USA, during August 2126, 2023.





The total of 43 regular papers presented in this book were carefully selected from 60 submissions. 





Part I contains 22 regular papers that stem from the following workshops:





ICDAR 2023 Workshop on Computational Paleography (IWCP);





ICDAR 2023 Workshop on Camera-Based Document Analysis and Recognition (CBDAR);





ICDAR 2023 International Workshop on Graphics Recognition (GREC);





ICDAR 2023 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA);





Part II contains 21 regular papers that stem from the following workshops:





ICDAR 2023 Workshop on Machine Vision and NLP for Document Analysis (VINALDO);





ICDAR 2023 International Workshop on MachineLearning (WML).





 
Typefaces and Ligatures in Printed Arabic Text: A Deep Learning-Based
OCR Perspective.- Leveraging Knowledge Graph Embeddings to Enhance Contextual
Representations for Relation Extraction.- Extracting Key-Value Pairs in
Business Documents.- Long-Range Transformer Architectures for Document
Understanding.-Pre-training transformers  for Corporate Documents
Understanding.- Transformer-Based Neural Machine Translation for Post-OCR
Error Correction in Cursive Text.- Arxiv Tables: Document Understanding
Challenge Linking Texts and Tables.- Subgraph-Induced Extraction Technique
for Information (SETI) from Administrative Documents.- Document Layout
Annotation: Database and Benchmark in the Domain of Public Affairs.- A
Clustering Approach Combining Lines and Text Detection for Table Extraction.-
Absformer: Transformer-Based Model for Unsupervised Multi-Document
Abstractive Summarization.- A Comparison of Demographic Attributes Detection
from Handwriting Based on Traditional and Deep Learning Methods.- A New
Optimization Approach to Improve an Ensemble Learning Model: Application to
Persian/Arabic Handwritten Character Recognition.- BN-DRISHTI: Bangla
Document Recognition Through Instance-level Segmentation of Handwritten Text
Images.- Text Line Detection and Recognition of Greek Polytonic Documents.- A
Comprehensive Handwritten Paragraph Text Recognition System: LexiconNet.-
Local Style Awareness of Font Images.- Fourier Feature-Based CBAM and Vision
Transformer for Text Detection in Drone Images.- Document Binarization with
Quaternionic Double Discriminator Generative Adversarial Network.-
Crosslingual Handwritten Text Generation Using GANs.- Knowledge Integration
inside Multitask Network for Analysis of Unseen ID Types.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97830314150126e.html
Märksõnad: