J. M. Górriz

288 papers receiving 8.6k citations

J. M. Górriz's Hit Papers

Deep learning in food category recognition 2023 · 245 citations
2450+2+4Years since publication100200300

Peers

J. M. Górriz
Comparison fields: 5 of 192
  • Neurology 2.0k
  • Health Informatics 189
  • Health Information Management 592
  • Computer Vision and Pattern Recognition 2.4k
  • Cognitive Neuroscience 1.7k
Replace Heung‐Il Suk with:
Heung‐Il Suk South Korea
Daoqiang Zhang China
Baiying Lei China
Shuihua Wang‎ China
Javier Ramı́rez Spain
Jasjit S. Suri United States
Dagan Feng Australia
Xiaofeng Zhu China
Ayman El‐Baz United States
Seong‐Whan Lee South Korea
J. M. Górriz relative to Heung‐Il Suk South Korea Heung‐Il Suk's profile →
Citations per field
00.5×3.3×
Heung‐Il Suk · 1×
Citations per year

Countries citing papers authored by J. M. Górriz

Since Specialization
Citations

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

Fields of papers citing papers by J. M. Górriz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. M. Górriz. 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 J. M. Górriz. The network helps show where J. M. Górriz may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 297 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation
Hit paper breakdown →
2020313
2 2016288
3
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
Hit paper breakdown →
2020277
4
Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network
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2020260
5
Deep learning in food category recognition
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2023245
6 2014191
7 2021165
8 2019154
9 2021141
10 2021127
11 2017123
12 2010122
13 2011121
14 2009116
15 2021113
16 2012110
17 2009107
18
Emotion recognition in EEG signals using deep learning methods: A review
Hit paper breakdown →
2023107
19 2021107
20 2010104

About J. M. Górriz

J. M. Górriz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 297 papers that have together received 9.0k indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (66 papers), Medical Image Segmentation Techniques (53 papers), Blind Source Separation Techniques (37 papers), Functional Brain Connectivity Studies (33 papers), Image Retrieval and Classification Techniques (33 papers), AI in cancer detection (26 papers), Spectroscopy and Chemometric Analyses (25 papers) and Dementia and Cognitive Impairment Research (24 papers). The work is most often cited by research in Neurology (2.0k citations), Health Informatics (189 citations), Health Information Management (592 citations), Computer Vision and Pattern Recognition (2.4k citations) and Cognitive Neuroscience (1.7k citations). J. M. Górriz has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Javier Ramı́rez, D. Salas-González, Yudong Zhang, I. Álvarez, Andrés Ortíz, F. Segovia, Shuihua Wang‎, Carlos G. Puntonet, Francisco J. Martínez-Murcia and M. López. Their work appears in journals such as International Journal of Neural Systems, Neurocomputing, Expert Systems with Applications, Information Fusion and Electronics Letters.

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.

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