A survey image classification using convolutional neural network in deep learning
Fathima Ghouse, Rashmika · 2023
The processing of image data for transmission and machine perception, in addition to providing enhanced visual data for human simplification, makes image processing an always fascinating field. Digital images can be made better through the use of image processing. Grayscale conversion, image segmentation, edge detection, feature extraction, and classification are all methods of image processing. The current deep learning convolutional neural network-based image classification system is discussed in detail in this chapter. The fundamental motivation behind the work introduced in this chapter is to think about and examine the various models involving convolutional brain network in profound learning for picture grouping. DenseNet, MobileNet, VGGnet, GoogleNet, ResNet, ImageNet, NasNet, and AlexNet were among the standard models that the algorithm was applied to. The most famous convolutional brain network is utilized for object discovery and item classification groupings from pictures are AlexNet, GoogleNet, and ResNet. Generally, the chapter gives definite information on picture handling and order strategies.