Semi-lexical languages: a formal basis for using domain knowledge to resolve ambiguities in deep-learning based computer vision-Reference-Cited by-同舟云学术

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Semi-lexical languages: a formal basis for using domain knowledge to resolve ambiguities in deep-learning based computer vision

Published:2021-12 Issue: Volume:152 Page:143-149
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Gangopadhyay Briti,Hazra Somnath,Dasgupta Pallab

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference28 articles.

1. A survey of deep neural network architectures and their applications;Liu;Neurocomputing,2017

2. Deep residual learning for image recognition;He,2016

3. Rich feature hierarchies for accurate object detection and semantic segmentation;Girshick,2014

4. Yolov3: an incremental improvement;Redmon;CoRR,2018

5. Analysing mathematical reasoning abilities of neural models;Saxton,2019

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1. A comparative analysis of knowledge injection strategies for large language models in the scholarly domain;Engineering Applications of Artificial Intelligence;2024-07

2. A Survey of Knowledge Enhanced Pre-trained Language Models;ACM Transactions on Asian and Low-Resource Language Information Processing;2024-03

3. Deep feature extraction with tri-channel textual feature map for text classification;Pattern Recognition Letters;2024-02

4. World on Data Perspective;World;2022-09-12

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