Browse > Computer Vision > Image Classification

Image Classification

330 papers with code · Computer Vision

State-of-the-art leaderboards

Greatest papers with code

Learning Transferable Architectures for Scalable Image Recognition

CVPR 2018 tensorflow/models

In our experiments, we search for the best convolutional layer (or "cell") on the CIFAR-10 dataset and then apply this cell to the ImageNet dataset by stacking together more copies of this cell, each with their own parameters to design a convolutional architecture, named "NASNet architecture".

ARCHITECTURE SEARCH IMAGE CLASSIFICATION

The iNaturalist Species Classification and Detection Dataset

CVPR 2018 tensorflow/models

Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories.

IMAGE CLASSIFICATION

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

17 Apr 2017tensorflow/models

We present a class of efficient models called MobileNets for mobile and embedded vision applications.

IMAGE CLASSIFICATION OBJECT DETECTION

Xception: Deep Learning with Depthwise Separable Convolutions

CVPR 2017 tensorflow/models

We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution).

IMAGE CLASSIFICATION

Wide Residual Networks

23 May 2016tensorflow/models

Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance.

IMAGE CLASSIFICATION

Identity Mappings in Deep Residual Networks

16 Mar 2016tensorflow/models

Deep residual networks have emerged as a family of extremely deep architectures showing compelling accuracy and nice convergence behaviors.

IMAGE CLASSIFICATION

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

23 Feb 2016tensorflow/models

Recently, the introduction of residual connections in conjunction with a more traditional architecture has yielded state-of-the-art performance in the 2015 ILSVRC challenge; its performance was similar to the latest generation Inception-v3 network.

IMAGE CLASSIFICATION

Deep Residual Learning for Image Recognition

CVPR 2016 tensorflow/models

Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

IMAGE CLASSIFICATION OBJECT DETECTION

Rethinking the Inception Architecture for Computer Vision

CVPR 2016 tensorflow/models

Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks.

IMAGE CLASSIFICATION

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

11 Feb 2015tensorflow/models

Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change.

IMAGE CLASSIFICATION