Vision Outlooker architecture sets a record for image classification accuracy without pre-training

27 June 2021

Vision Outlooker architecture sets a record for image classification accuracy without pre-training

Vision Outlooker (VOLO) is a variation of the Vision Transformer architecture. Designed to reduce reliance on additional training data, VOLO reached a record 87.1% on ImageNet without pre-training. The code…

SEER: a self-supervised neural network with a billion parameters from FAIR

9 March 2021

SEER: a self-supervised neural network with a billion parameters from FAIR

SEER is FAIR’s self-supervised billion-parameter neural network for computer vision applications. The model pre-trained on the Instagram pictures can be further trained on your tasks. The developers have published the…

VGG16 – Convolutional Network for Classification and Detection

20 November 2018
vgg16

VGG16 – Convolutional Network for Classification and Detection

VGG16 is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper “Very Deep Convolutional Networks for Large-Scale Image Recognition”.…

AlexNet – ImageNet Classification with Deep Convolutional Neural Networks

29 October 2018

AlexNet – ImageNet Classification with Deep Convolutional Neural Networks

AlexNet is the name of a convolutional neural network which has had a large impact on the field of machine learning, specifically in the application of deep learning to machine vision. It famously won the…

Deep Clustering Approach for Image Classification Task

20 September 2018
deepcluster facebook

Deep Clustering Approach for Image Classification Task

The clustering of images seems to be a well-researched topic. But in fact, little work has been done to adapt it to the end-to-end training of visual features on large-scale…