ImageNet classification with deep convolutional neural networks2017 · 47.3k citations
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
2017Communications of the ACM
2014Journal of Machine Learning Research
2011The European Symposium on Artificial Neural Networks
Countries citing papers authored by Alex Krizhevsky
Since Specialization
Citations
This map shows the geographic impact of Alex Krizhevsky's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alex Krizhevsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Krizhevsky more than expected).
This network shows the impact of papers produced by Alex Krizhevsky. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alex Krizhevsky. The network helps show where Alex Krizhevsky may publish in the future.
Co-authors
The 10 scholars most cited alongside Alex Krizhevsky, linked wherever they
have co-authored with each other. Click a name or a connecting line to browse the papers
they share.
Border = papers with Alex KrizhevskyLine = papers co-authored togetherAlex Krizhevsky links everyone, so they are left out of the graph.
All Works
7 of 7 papers shown
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Work
1
ImageNet classification with deep convolutional neural networks
Alex Krizhevsky is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Automotive Engineering, Infectious Diseases and Organic Chemistry, having authored 7 papers that have together received 70.5k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (2 papers), Anomaly Detection Techniques and Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Neural Networks and Applications (1 paper), Advanced Image Processing Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (31.3k citations), Artificial Intelligence (24.9k citations), Media Technology (5.3k citations), Signal Processing (5.1k citations) and Health Informatics (384 citations). Alex Krizhevsky has collaborated with scholars based in Canada and United States. Frequent co-authors include Geoffrey E. Hinton, Ilya Sutskever, Nitish Srivastava, Ruslan Salakhutdinov, Vincent Vanhoucke, Anelia Angelova, Abhijit S. Ogale, Marc’Aurelio Ranzato, Dave Ferguson and Mayank Bansal. Their work appears in journals such as Communications of the ACM, Journal of Machine Learning Research, International Conference on Artificial Intelligence and Statistics, arXiv (Cornell University) and The European Symposium on Artificial Neural Networks.
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