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Image Analytics to Detect Cigarette in an Image Using Deep Learning

机译:图像分析以使用深度学习检测图像中的香烟

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Significant number of modern films depict some form of tobacco use, but rarely depict its real-life consequences such as addiction, illness and death. As per [1], anti-tobacco health warnings are mandatory for scenes depicting smoking scenes. In this paper, an automated recognition system is proposed to identify images with smoking activities and tag them accordingly. The proposed approach implements the technique of object detection based on deep learning. Convolutional neural network is used to generate feature maps from the images. These machine-learnt features are used to classify the images. The system can detect the smoking events of uncertain actions with various cigarette sizes, colors and shapes. We have experimented our work by applying the proposed approach to two real-world datasets and that have demonstrated the effectiveness of our solution with a decent model accuracy.
机译:大量现代薄膜描绘了某种形式的烟草使用,但很少描述其现实生活后果,例如成瘾,疾病和死亡。 根据[1],对描绘吸烟场景的场景是强制性的,防烟卫生警告是强制性的。 在本文中,提出了一种自动识别系统,以识别具有吸烟活动的图像并相应地标记它们。 所提出的方法基于深度学习实现了对象检测技术。 卷积神经网络用于从图像生成特征映射。 这些机器学习功能用于对图像进行分类。 该系统可以检测具有各种卷烟尺寸,颜色和形状的不确定动作的吸烟事件。 我们通过将建议的方法应用于两个现实世界数据集,并以体面的模型准确性展示了我们解决方案的有效性来试验了我们的工作。

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