Relational Reasoning Using Neural Networks: A Survey

Author:

Pise Anil Audumbar1ORCID,Vadapalli Hima1,Sanders Ian2

Affiliation:

1. School of Computer Science and Applied Mathematics, University of the Witwatersrand, South Africa

2. Department of Computer Science, University of South Africa, South Africa

Abstract

Relational Networks (RN), as one of the most widely used relational reasoning techniques, have achieved great success in many applications such as action and image analysis, speech recognition and text understanding. The use of relational reasoning via RN in neural networks has often been used in recent years. In these instances, RN is composed of various deep learning-based algorithms in simple plug-and-play modules. This is quite advantageous since it circumvents the need for features engineering. This paper surveys the emerging research of deep learning models that make use of RN in tasks such as Natural Language Processing (NLP), Action Recognition, Temporal Relational Reasoning as well as Facial Emotion Recognition (FER). Since, RNs are easy to integrate they have been used in various tasks such as NLP, Recurrent Neural Networks (RNN), Action Recognition, Image Analysis, Object Detection, Temporal Relational Reasoning, as well as for FER. This is due to the fact that RNs use bidirectional LSTM and CNN to solve relational reasoning problems at character and word level. In this paper a comparative review of all relational reasoning-based RN models using deep learning techniques is presented.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare;Robotics;2024-07-23

2. An Enhanced Method for Recognition of Facial Expressions using Convolutional Neural Network;2024 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV);2024-03-11

3. RGRN: Relation-aware graph reasoning network for object detection;Neural Computing and Applications;2023-04-20

4. Automation of System Infrastructure Upgrade or Downgrade Using AI;Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence;2023-04-07

5. Performance Analysis of Deep Learning Algorithms in Diagnosis of Malaria Disease;Diagnostics;2023-02-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3