IMAGE SEGMENTATION USING DEEP LEARNING TECHNIQUES

IMAGE SEGMENTATION USING DEEP LEARNING TECHNIQUES

G.Mythri Sri, G. Naga Thanishq Reddy, G. Nikhitha, G. Nithin Kumar
AI&ML, Malla Reddy University

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Abstract: Color image segmentation is an important task in computer vision, which involves partitioning an image into different regions based on their color similarity. In recent years, deep learning has emerged as a powerful tool for image segmentation. The use of convolutional neural networks (CNNs) has shown promising results in various applications, including color image segmentation. The process of color image segmentation using deep learning typically involves training a CNN on a large dataset of labeled images, where each pixel in the image is assigned, a label corresponding to its segment. During training, the network learns to extract features from the input image and use them to classify each pixel into its corresponding segment. The trained network can then be used to segment new images.

Key Words: Image segmentation, Convolutional Neural Networks (CNNs), Numerical digits, Recognition accuracy, robustness, Computational efficiency,  Pre-processing techniques, Communication accessibility, Assistive technology.