1.4k citations · 1.8k across the 3 of their papers we have counts for
3 papers
Attention for Fine-Grained Categorization
Pierre Sermanet, Andrea Frome, Esteban Real
This paper presents experiments extending the work of Ba et al. (2014) on recurrent neural models for attention into less constrained visual environments, specifically fine-grained…
Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
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 th…
Convolutional Neural Networks Applied to House Numbers Digit Classification
Pierre Sermanet, Soumith Chintala, Yann LeCun
We classify digits of real-world house numbers using convolutional neural networks (ConvNets). ConvNets are hierarchical feature learning neural networks whose structure is biologi…