RETRACTED: Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms (Retracted Article)

被引:0
|
作者
Ajay, P. [1 ]
Nagaraj, B. [2 ]
Huang, Ruihang [3 ]
Raj, M. S. Pradeep [2 ]
Ananthi, P. [4 ]
机构
[1] Anna Univ, Fac Informat & Commun Engn, Chennai, Tamil Nadu, India
[2] Rathinam Tech Campus, Dept Elect & Commun Engn, Coimbatore, Tamil Nadu, India
[3] Donghua Univ, Shanghai, Peoples R China
[4] Rathinam Tech Campus, Dept Artificial Intelligence & Data Sci, Coimbatore, Tamil Nadu, India
关键词
DEEP; PLACE;
D O I
10.1155/2022/4989248
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Intelligent machines have grown in importance in recent years in object recognition in terms of their ability to envision, comprehend, and reach decisions. There are a lot of complicated algorithms that accomplish AI utilities. In addition to their use in the medical industry, these methods of object recognition have a wide range of other fields, most notably industries, in which they can be applied. In contrast to the proposed calculation, the proposed calculation is less complex and more accurate under certain SNR conditions. In the deep nervous tissue fine-tuning discriminator, phantom highlights and binding highlights are separated as sources; modified direct components are used as neuronal activation abilities; and cross entropy is used as unfortunate abilities. Optimized recognition of profound nervous tissue builds profound and periodic nervous tissue for regulatory confirmation of the corresponding signal.
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页数:8
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