一种用于糖尿病视网膜病变检测与分级的混合CNN深度特征提取模型

IF 1 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal on Artificial Intelligence Tools Pub Date : 2023-03-22 DOI:10.1142/s0218213023500367

N. Mukherjee, S. Sengupta

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Hybrid CNN Model for Deep Feature Extraction for Diabetic Retinopathy Detection and Gradation

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来源期刊

International Journal on Artificial Intelligence Tools 工程技术-计算机：跨学科应用

CiteScore

2.10

自引率

9.10%

发文量

审稿时长

8.5 months

期刊介绍： The International Journal on Artificial Intelligence Tools (IJAIT) provides an interdisciplinary forum in which AI scientists and professionals can share their research results and report new advances on AI tools or tools that use AI. Tools refer to architectures, languages or algorithms, which constitute the means connecting theory with applications. So, IJAIT is a medium for promoting general and/or special purpose tools, which are very important for the evolution of science and manipulation of knowledge. IJAIT can also be used as a test ground for new AI tools. Topics covered by IJAIT include but are not limited to: AI in Bioinformatics, AI for Service Engineering, AI for Software Engineering, AI for Ubiquitous Computing, AI for Web Intelligence Applications, AI Parallel Processing Tools (hardware/software), AI Programming Languages, AI Tools for CAD and VLSI Analysis/Design/Testing, AI Tools for Computer Vision and Speech Understanding, AI Tools for Multimedia, Cognitive Informatics, Data Mining and Machine Learning Tools, Heuristic and AI Planning Strategies and Tools, Image Understanding, Integrated/Hybrid AI Approaches, Intelligent System Architectures, Knowledge-Based/Expert Systems, Knowledge Management and Processing Tools, Knowledge Representation Languages, Natural Language Understanding, Neural Networks for AI, Object-Oriented Programming for AI, Reasoning and Evolution of Knowledge Bases, Self-Healing and Autonomous Systems, and Software Engineering for AI.