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5. ImageNet and the Rise of ConvNets
This text discusses the history and impact of convolutional neural networks (ConvNets) in computer vision, specifically focusing on their role in the ImageNet competition. It highlights the pivotal role of Yann LeCun's work on ConvNets,
their initial struggles, and their eventual triumph in 2012 due to
increased computing power and the availability of the massive ImageNet
dataset. The creation of ImageNet itself is detailed, emphasizing Fei-Fei Li's innovative use of Amazon Mechanical Turk for image labeling. The text further explores the implications of the ImageNet competition, including a cheating scandal and the subsequent rapid adoption of ConvNets by tech companies. Finally, it examines the limitations of current ConvNets in comparison to human object recognition abilities, concluding that while significant progress has been made, true visual intelligence remains a distant goal.
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By Chris GuoThis text discusses the history and impact of convolutional neural networks (ConvNets) in computer vision, specifically focusing on their role in the ImageNet competition. It highlights the pivotal role of Yann LeCun's work on ConvNets,
their initial struggles, and their eventual triumph in 2012 due to
increased computing power and the availability of the massive ImageNet
dataset. The creation of ImageNet itself is detailed, emphasizing Fei-Fei Li's innovative use of Amazon Mechanical Turk for image labeling. The text further explores the implications of the ImageNet competition, including a cheating scandal and the subsequent rapid adoption of ConvNets by tech companies. Finally, it examines the limitations of current ConvNets in comparison to human object recognition abilities, concluding that while significant progress has been made, true visual intelligence remains a distant goal.