José Cano

34 papers receiving 192 citations

Peers

José Cano
Comparison fields: 5 of 40
  • Computational Mathematics 6
  • Hardware and Architecture 39
  • Computer Vision and Pattern Recognition 73
  • Artificial Intelligence 95
  • Computer Networks and Communications 66
Replace Shaofeng H.-C. Jiang with:
Shaofeng H.-C. Jiang China
Nikita Mishra United States
Mohammad Sadegh Talebi Iran
Alan Soper United Kingdom
Yang Su China
Pino Persiano Italy
L. S. S. Reddy India
Yingke Chen China
Rajendra Kumar India
José Cano relative to Shaofeng H.-C. Jiang China Shaofeng H.-C. Jiang's profile →
Citations per field
00.5×1.5×
Shaofeng H.-C. Jiang · 1×
Citations per year

Countries citing papers authored by José Cano

Since Specialization
Citations

This map shows the geographic impact of José Cano'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 José Cano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Cano more than expected).

Fields of papers citing papers by José Cano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Cano. 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 José Cano. The network helps show where José Cano may publish in the future.

Co-authors

The 25 scholars most cited alongside José Cano, 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 José Cano Line = papers co-authored together José Cano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199337
2 201925
3 201818
4
Accelerating Deep Neural Networks on Low Power Heterogeneous Architectures
201812
5 201210
6 20189
7 20228
8 20208
9 20217
10 20187
11 20247
12 20106
13 20226
14 20155
15 20224
16 20164
17 20064
18 20164
19 20233
20 20252

About José Cano

José Cano is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture and Electrical and Electronic Engineering, having authored 37 papers that have together received 207 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Parallel Computing and Optimization Techniques (11 papers), Adversarial Robustness in Machine Learning (7 papers), Interconnection Networks and Systems (5 papers), Embedded Systems Design Techniques (4 papers), Advanced Memory and Neural Computing (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Opportunistic and Delay-Tolerant Networks (3 papers). The work is most often cited by research in Computational Mathematics (6 citations), Hardware and Architecture (39 citations), Computer Vision and Pattern Recognition (73 citations), Artificial Intelligence (95 citations) and Computer Networks and Communications (66 citations). José Cano has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include Serafı́n Moral, Miguel Delgado, Michael O’Boyle, Elliot J. Crowley, Valentin Radu, Amos Storkey, Jack Turner, Vijay Nagarajan, Michael O’Boyle and José Flich. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, Journal of Parallel and Distributed Computing, Autonomous Robots, IEEE Transactions on Computers and International Journal of Approximate Reasoning.

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.

Explore authors with similar magnitude of impact