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ImageNet: A large-scale hierarchical image database
https://ieeexplore.ieee.org/document/5206848
WEBThis paper offers a detailed analysis of ImageNet in its current state: 12 subtrees with 5247 synsets and 3.2 million images in total. We show that ImageNet is much larger in scale and diversity and much more accurate than the current image datasets.
DA: 96 PA: 11 MOZ Rank: 90
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[1409.0575] ImageNet Large Scale Visual Recognition Challenge
https://arxiv.org/abs/1409.0575
WEBSep 1, 2014 · This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field …
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ImageNet
https://image-net.org/
WEBImageNet is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images. The project has been instrumental in advancing computer vision and deep learning research.
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ImageNet Dataset | Papers With Code
https://paperswithcode.com/dataset/imagenet
WEBThe ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.
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ImageNet - Wikipedia
https://en.wikipedia.org/wiki/ImageNet
WEBThe ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
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(PDF) ImageNet: a Large-Scale Hierarchical Image Database
https://www.researchgate.net/publication/221361415_ImageNet_a_Large-Scale_Hierarchical_Image_Database
WEBJun 1, 2009 · This paper offers a detailed analysis of ImageNet in its current state: 12 subtrees with 5247 synsets and 3.2 million images in total. We show that ImageNet is much larger in scale and...
DA: 13 PA: 35 MOZ Rank: 4
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[1409.4842] Going Deeper with Convolutions - arXiv.org
https://arxiv.org/abs/1409.4842
WEBSep 17, 2014 · Going Deeper with Convolutions. 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).
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What makes ImageNet good for transfer learning? - arXiv.org
https://arxiv.org/pdf/1608.08614.pdf
WEBThe paper is organized as a set of experiments answering a list of key questions about feature learning with ImageNet. The following is a summary of our main findings: 1. How many pre-training ImageNet examples are sufficient for transfer learning?
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ImageNet classification with deep convolutional neural networks
https://dl.acm.org/doi/10.1145/3065386
WEBMay 24, 2017 · In this paper, we presented an automated system for identification and classification of fish species. It helps the marine biologists to have greater understanding of the fish species and their habitats. The proposed model is based on deep ...
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Do Better ImageNet Models Transfer Better? Paper Summary
https://cornell-data.medium.com/do-better-imagenet-models-transfer-better-paper-summary-analysis-3e6ff3a0a2e6
WEBMay 5, 2021 · Cornell Data Science. ·. Follow. 3 min read. ·. May 5, 2021. 3. Paper:...
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