Rahul Dubey*, Jitendra Agrawal
Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 747-763, 2022, DOI:10.32604/iasc.2022.020975
Abstract Extracting the features from an image is a cumbersome task. Initially, this task was performed by domain experts through a process known as handcrafted feature design. A deep embedding technique known as convolutional neural networks (CNNs) later solved this problem by introducing the feature learning concept, through which the CNN is directly provided with images. This CNN then learns the features of the image, which are subsequently given as input to the further layers for an intended task like classification. CNNs have demonstrated astonishing performance in several practicable applications in the last few years. Nevertheless, the pursuance of CNNs primarily… More >
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