Automatic Image Annotation Using Adaptive Convolutional Deep Learning Model  

作　　者：R.Jayaraj S.Lokesh 

机构地区：[1]Department of Computer Science and Engineering,Hindusthan College of Engineering and Technology,Coimbatore,641032,Tamilnadu,India [2]Department of Computer Science and Engineering,Hindusthan Institute of Technology,Coimbatore,641032,Tamilnadu,India

出　　处：《Intelligent Automation & Soft Computing》2023年第4期481-497,共17页智能自动化与软计算（英文）

摘　　要：Every day,websites and personal archives create more and more photos.The size of these archives is immeasurable.The comfort of use of these huge digital image gatherings donates to their admiration.However,not all of these folders deliver relevant indexing information.From the outcomes,it is dif-ficult to discover data that the user can be absorbed in.Therefore,in order to determine the significance of the data,it is important to identify the contents in an informative manner.Image annotation can be one of the greatest problematic domains in multimedia research and computer vision.Hence,in this paper,Adap-tive Convolutional Deep Learning Model(ACDLM)is developed for automatic image annotation.Initially,the databases are collected from the open-source system which consists of some labelled images(for training phase)and some unlabeled images{Corel 5 K,MSRC v2}.After that,the images are sent to the pre-processing step such as colour space quantization and texture color class map.The pre-processed images are sent to the segmentation approach for efficient labelling technique using J-image segmentation(JSEG).Thefinal step is an auto-matic annotation using ACDLM which is a combination of Convolutional Neural Network(CNN)and Honey Badger Algorithm(HBA).Based on the proposed classifier,the unlabeled images are labelled.The proposed methodology is imple-mented in MATLAB and performance is evaluated by performance metrics such as accuracy,precision,recall and F1_Measure.With the assistance of the pro-posed methodology,the unlabeled images are labelled.

关 键 词：Deep learning model J-image segmentation honey badger algorithm convolutional neural network image annotation 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]