Adnan Ahmed Rafique1, Yazeed Yasin Ghadi2, Suliman A. Alsuhibany3, Samia Allaoua Chelloug4,*, Ahmad Jalal1, Jeongmin Park5
CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4657-4675, 2022, DOI:10.32604/cmc.2022.027720
Abstract Latest advancements in vision technology offer an evident impact on multi-object recognition and scene understanding. Such scene-understanding task is a demanding part of several technologies, like augmented reality-based scene integration, robotic navigation, autonomous driving, and tourist guide. Incorporating visual information in contextually unified segments, convolution neural networks-based approaches will significantly mitigate the clutter, which is usual in classical frameworks during scene understanding. In this paper, we propose a convolutional neural network (CNN) based segmentation method for the recognition of multiple objects in an image. Initially, after acquisition and preprocessing, the image is segmented by using… More >
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