HU‐PageScan: a fully convolutional neural network for document page crop

Author:

Neves Ricardo Batista1,Lima Estanislau1,Bezerra Byron L.D.1ORCID,Zanchettin Cleber23,Toselli Alejandro H.4

Affiliation:

1. Universidade de PernambucoR. Benfica, 455 – MadalenaRecifePE50720‐001Brazil

2. Centro de InformáticaUniversidade Federal de PernambucoRecifeBrazil

3. Department of Chemical and Biological EngineeringNorthwestern UniversityEvanstonUSA

4. PRHLT Research CenterUniversitat Politécnica de ValénciaCamí de Vera, s/n46022ValénciaSpain

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

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2. DocLightDetect: A New Algorithm for Occlusion Classification in Identification Documents;Lecture Notes in Computer Science;2024

3. A Robust Approach to Detect Occlusions During Camera-Based Document Scanning;2023 IEEE Latin American Conference on Computational Intelligence (LA-CCI);2023-10-29

4. Self-calibrated U-Net for Document Segmentation;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

5. LDRNet: Enabling Real-Time Document Localization on Mobile Devices;Communications in Computer and Information Science;2023

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