Davide Testuggine

541 citations
2 papers · 88 · h-index 2

Impact in

    • Sentiment Analysis and Opinion Mining
    • Topic Modeling
    • Domain Adaptation and Few-Shot Learning
    • Anomaly Detection Techniques and Applications
    • Multimodal Machine Learning Applications
    • Human Pose and Action Recognition
    • Advanced Image and Video Retrieval Techniques

Papers in

Journals
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (1 paper)
Partner nations
United States

In The Last Decade

Davide Testuggine

2 papers receiving 86 citations

Peers

Davide Testuggine
Comparison fields: 5 of 35
  • Artificial Intelligence 60
  • Computer Vision and Pattern Recognition 37
  • Signal Processing 12
  • Health Informatics 1
  • Experimental and Cognitive Psychology 6
Replace Shelly Sheynin with:
Shelly Sheynin Israel
Badri N. Patro India
Yonatan Geifman Israel
Gabriele Graffieti Italy
Lewei Lu Hong Kong
Taihong Xiao United States
Byungseok Roh Japan
Shagun Sodhani Canada
Eran Malach Israel
Chen-Yu Lee Taiwan
Davide Testuggine relative to Shelly Sheynin Israel Shelly Sheynin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Davide Testuggine

Since Specialization
Citations

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

Fields of papers citing papers by Davide Testuggine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Davide Testuggine, 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 Davide Testuggine Line = papers co-authored together Davide Testuggine links everyone, so they are left out of the graph.

All Works

2 of 2 papers shown
#Work
1 202286
2
Supervised Multimodal Bitransformers for Classifying Images and Text.
20192

About Davide Testuggine

Davide Testuggine is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering, Signal Processing, Artificial Intelligence and Infectious Diseases, having authored 2 papers that have together received 88 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Infrastructure Maintenance and Monitoring (1 paper), Text and Document Classification Technologies (1 paper), Music and Audio Processing (1 paper) and Handwritten Text Recognition Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (60 citations), Computer Vision and Pattern Recognition (37 citations), Signal Processing (12 citations), Health Informatics (1 citation) and Experimental and Cognitive Psychology (6 citations). Davide Testuggine has collaborated with scholars based in United States. Frequent co-authors include Xi Peng, L. Zhao, Mengmeng Ma, Jian Ren, Douwe Kiela and Hamed Firooz. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

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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