Neuro-Symbolic Learning: Principles and Applications in Ophthalmology

التفاصيل البيبلوغرافية
العنوان: Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
المؤلفون: Hassan, Muhammad, Guan, Haifei, Melliou, Aikaterini, Wang, Yuqi, Sun, Qianhui, Zeng, Sen, Liang, Wen, Zhang, Yiwei, Zhang, Ziheng, Hu, Qiuyue, Liu, Yang, Shi, Shunkai, An, Lin, Ma, Shuyue, Gul, Ijaz, Rahee, Muhammad Akmal, You, Zhou, Zhang, Canyang, Pandey, Vijay Kumar, Han, Yuxing, Zhang, Yongbing, Xu, Ming, Huang, Qiming, Tan, Jiefu, Xing, Qi, Qin, Peiwu, Yu, Dongmei
سنة النشر: 2022
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
الوصف: Neural networks have been rapidly expanding in recent years, with novel strategies and applications. However, challenges such as interpretability, explainability, robustness, safety, trust, and sensibility remain unsolved in neural network technologies, despite the fact that they will unavoidably be addressed for critical applications. Attempts have been made to overcome the challenges in neural network computing by representing and embedding domain knowledge in terms of symbolic representations. Thus, the neuro-symbolic learning (NeSyL) notion emerged, which incorporates aspects of symbolic representation and bringing common sense into neural networks (NeSyL). In domains where interpretability, reasoning, and explainability are crucial, such as video and image captioning, question-answering and reasoning, health informatics, and genomics, NeSyL has shown promising outcomes. This review presents a comprehensive survey on the state-of-the-art NeSyL approaches, their principles, advances in machine and deep learning algorithms, applications such as opthalmology, and most importantly, future perspectives of this emerging field.
Comment: 24 pages, 16 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2208.00374
رقم الأكسشن: edsarx.2208.00374
قاعدة البيانات: arXiv