Requirements: .ePUB, .PDF reader, 32.9 MB
Overview: This book presents the current trends in Deep Learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using Deep Learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues. In recent years, there has been a notable transition from rule-based Artificial Intelligence (AI) to Machine-Learning-based AI, with an increasing focus on Deep Learning. Currently, Deep Learning frameworks are at the forefront of AI technology, marking significant advancements in academic and industrial fields. The evolution of deep convolutional neural networks (CNNs) has positioned deep learning as the method of choice for computer vision tasks, including image classification, segmentation, object detection, and human keypoint detection. This surge in Deep Learning has sparked interest in applying Convolutional Neural Networks (CNNs) across various domains, including the task of logo detection. The book is directed to professors, researchers, practitioners in the field of engineering, Computer Science, and related fields as well as anyone interested in using Deep Learning techniques and applications in logo and various object detection tasks.
Genre: Non-Fiction > Tech & Devices
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