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Application of Deep Learning for Object Detection

机译:深度学习在目标检测中的应用

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摘要

The ubiquitous and wide applications like scene understanding, video surveillance, robotics, and self-driving systems triggered vast research in the domain of computer vision in the most recent decade. Being the core of all these applications, visual recognition systems which encompasses image classification, localization and detection have achieved great research momentum. Due to significant development in neural networks especially deep learning, these visual recognition systems have attained remarkable performance. Object detection is one of these domains witnessing great success in computer vision. This paper demystifies the role of deep learning techniques based on convolutional neural network for object detection. Deep learning frameworks and services available for object detection are also enunciated. Deep learning techniques for state-of-the-art object detection systems are assessed in this paper.
机译:在最近十年中,诸如场景理解,视频监控,机器人技术和自动驾驶系统等无处不在的广泛应用引发了计算机视觉领域的大量研究。作为所有这些应用程序的核心,涵盖图像分类,定位和检测的视觉识别系统取得了巨大的研究动力。由于神经网络特别是深度学习的显着发展,这些视觉识别系统已取得了卓越的性能。对象检测是在计算机视觉中获得巨大成功的这些领域之一。本文揭露了基于卷积神经网络的深度学习技术在对象检测中的作用。还阐明了可用于对象检测的深度学习框架和服务。本文评估了用于最新对象检测系统的深度学习技术。

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