2016 Ieee International Conference on Big Data (big Data) Deep Learning in the Automotive Industry: Applications and Tools

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Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, methodology): “In [78], visual inspection is investigated using CNN architectures including AlexNet and GoogLeNet over different platforms (Caffe, Tensorflow, and Torch).”
A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning (2019, background): “• Automotive Industry Luckow et al. [34] presented the applications and the tools for implementing deep neural networks in the auto-motive industry.”
Deep Metallic Surface Defect Detection: The New Benchmark and Detection Network (2020, background): “detection and other industrial applications, such as the automotive industry [2], fruit classification [3], and object detection [4,5].”
A Deep Learning Approach to Network Intrusion Detection (2018, background): “Deep learning is garnering significant interest and its application is being investigated within many research domains, such as: healthcare [11], [12]; automotive design [13], [14]; manufacturing [15] and law enforcement [16], [17].”
Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications (2018, background): “Architectures and models have been investigated in the past two decades, but availability of GPU computing enabled DL industrial applications such as automotive [1], control systems [2], fault detection and recovery [3], [4] and biomedicine [5], [6], just to mention some.”