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Deep trained features extraction and dense layer classification of sensitive and normal documents for robotic vision-based segregation

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Robotic vision automates segregation of sensitive and non-sensitive documents, highlighting deep learning's role.

Automating the classification of documents boosts access to important information using robotic vision technology.
Feature extraction using pre-trained deep learning models significantly improves accuracy and retrieval of sensitive data.
The methodology includes advanced deep learning techniques alongside machine learning for effective document segregation.
The proposed model demonstrates improved precision in identifying sensitive documents, suggesting valuable applications in security.

Khullar et al. (2024) studied this question.

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View Full Paper

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Authors

Robotic vision automates segregation of sensitive and non-sensitive documents, highlighting deep learning's role.

Automating the classification of documents boosts access to important information using robotic vision technology.
Feature extraction using pre-trained deep learning models significantly improves accuracy and retrieval of sensitive data.
The methodology includes advanced deep learning techniques alongside machine learning for effective document segregation.
The proposed model demonstrates improved precision in identifying sensitive documents, suggesting valuable applications in security.

Khullar et al. (2024) studied this question.

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