Task	Dataset	Model	Metric name	Metric value	Global rank
Image Classification	ImageNet	Inception V1	Top 1 Accuracy	69.8%	# 25
Image Classification	ImageNet	Inception V1	Top 5 Accuracy	89.9%	# 18
Object Detection	ImageNet Detection	Inception V1	MAP	43.9%	# 1

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Going Deeper with Convolutions

CVPR 2015 • Christian Szegedy • Wei Liu • Yangqing Jia • Pierre Sermanet • Scott Reed • Dragomir Anguelov • Dumitru Erhan • Vincent Vanhoucke • Andrew Rabinovich

We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC 2014). The main hallmark of this architecture is the improved utilization of the computing resources inside the network... (read more)

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IMAGE CLASSIFICATION

OBJECT DETECTION

OBJECT RECOGNITION

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SOTA for Object Detection on ImageNet Detection

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Task	Dataset	Model	Metric name	Metric value	Global rank	Compare
Image Classification	ImageNet	Inception V1	Top 1 Accuracy	69.8%	# 25	See all
Image Classification	ImageNet	Inception V1	Top 5 Accuracy	89.9%	# 18	See all
Object Detection	ImageNet Detection	Inception V1	MAP	43.9%	# 1	See all

Going Deeper with Convolutions

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