Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Gradient-based learning applied to document recognition
199834.5k citationsYann LeCun, Léon Bottou et al.Proceedings of the IEEEprofile →
Support vector machines for histogram-based image classification
19991.1k citationsOlivier Chapelle, Patrick Haffner et al.profile →
Countries citing papers authored by Patrick Haffner
Since
Specialization
Citations
This map shows the geographic impact of Patrick Haffner'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 Patrick Haffner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Haffner more than expected).
This network shows the impact of papers produced by Patrick Haffner. 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 Patrick Haffner. The network helps show where Patrick Haffner may publish in the future.
Co-authorship network of co-authors of Patrick Haffner
This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Haffner.
A scholar is included among the top collaborators of Patrick Haffner based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Patrick Haffner. Patrick Haffner is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Gupta, N. K., Giuseppe Di Fabbrizio, & Patrick Haffner. (2010). Capturing the Stars: Predicting Ratings for Service and Product Reviews. North American Chapter of the Association for Computational Linguistics. 36–43.23 indexed citations
Bottou, Léon, et al.. (2001). DjVu document browsing with on-demand loading and rendering of image components.1 indexed citations
14.
Chapelle, Olivier, et al.. (1999). SVMs for Histogram Based Image Classification. MPG.PuRe (Max Planck Society).132 indexed citations
15.
Simard, Patrice, Léon Bottou, Patrick Haffner, & Yann LeCun. (1998). Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. neural information processing systems. 11. 571–577.81 indexed citations
16.
LeCun, Yann, Léon Bottou, Yoshua Bengio, & Patrick Haffner. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE. 86(11). 2278–2324.34531 indexed citations breakdown →
17.
Haskell, Barry G., P.G. Howard, Yann LeCun, et al.. (1998). Image and video coding-emerging standards and beyond. IEEE Transactions on Circuits and Systems for Video Technology. 8(7). 814–837.55 indexed citations
Haffner, Patrick & Alex Waibel. (1991). Multi-State Time Delay Networks for Continuous Speech Recognition. Neural Information Processing Systems. 4. 135–142.25 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.