Image classification and retrieval using optimized Pulse-Coupled Neural Network
作者：
Highlights：
• We propose an image classification and retrieval technique using PCNN and K-NN.
• We optimized the PCNN parameters using genetic algorithm.
• We implemented a prototype to validate our proposed technique.
• The results are represented and measured with precision, recall and accuracy.
• The proposed technique proved its efficiency in classifying and retrieving images with comparison to other techniques.
摘要
•We propose an image classification and retrieval technique using PCNN and K-NN.•We optimized the PCNN parameters using genetic algorithm.•We implemented a prototype to validate our proposed technique.•The results are represented and measured with precision, recall and accuracy.•The proposed technique proved its efficiency in classifying and retrieving images with comparison to other techniques.
论文关键词：Content-Based Image Retrieval (CBIR),Image classification,Visual features,Pulse-Coupled Neural Network (PCNN),Image signature,K-Nearest Neighbor,Genetic algorithm
论文评审过程：Available online 24 February 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.02.019
