• Gorikapudi Mandheer
• Addanki Shiny Pavithra
• Chandika Bhavya
• Chennamsetty Anitha
• Andi Amrutha

Research on images is quite challenging nowadays since there are few techniques available to be used in the processing and classification of images. Classification of images based on contents is one of the most studied topics in computer vision. Today, this problem can be easily addressed with modern techniques such as Convolutional Neural Network data. Image classification is referred as Classification of the images from many predefined categories. Image classification is to input an image, and then use a certain classification algorithm to determine the category of the image. The main process of image classification: image preprocessing, image feature extraction and classifier design. Our system present Convolutional Neural Network (CNN), a machine learning algorithm being used for automatic classification the images. We will use the Blood cells data set as a bench mark for classification of the grayscale image. The grayscale images in the data set used for training that require more computational power for classification of images.

CNN, Object, Image Classification, Neutral Networks, Deep Learning

"IMAGE CLASSIFCATION USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.424-431, November-2024, Available :http://www.jetir.org/papers/JETIRGO06044.pdf

"IMAGE CLASSIFCATION USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp424-431, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06044.pdf