Matteo Stefanini

560 total citations · 1 hit paper
6 papers, 255 citations indexed

About

Matteo Stefanini is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Matteo Stefanini has authored 6 papers receiving a total of 255 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Matteo Stefanini's work include Multimodal Machine Learning Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Analysis and Summarization (2 papers). Matteo Stefanini is often cited by papers focused on Multimodal Machine Learning Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Analysis and Summarization (2 papers). Matteo Stefanini collaborates with scholars based in Italy. Matteo Stefanini's co-authors include Rita Cucchiara, Lorenzo Baraldi, Marcella Cornia, Silvia Cascianelli, Giuseppe Fiameni, Massimiliano Corsini, Elisa Ficarra, Fabrizio Falchi, Nicola Messina and Giuseppe Amato and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters and Computer Methods and Programs in Biomedicine.

In The Last Decade

Matteo Stefanini

6 papers receiving 248 citations

Hit Papers

align trajectories

What are hit papers?

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.

From Show to Tell: A Survey on Deep Learning-Based Image Captioning

2022 198 citations Matteo Stefanini, Marcella Cornia et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Matteo Stefanini Italy	5	209	108	11	8	7	6	255
Liunian Harold Li United States	8	112 0.5×	181 1.7×	16 1.5×	5 0.6×	6 0.9×	11	229
Belinda Zeng United States	6	176 0.8×	181 1.7×	14 1.3×	4 0.5×	5 0.7×	13	264
Tameem Adel United Kingdom	8	76 0.4×	146 1.4×	7 0.6×	12 1.5×	3 0.4×	16	192
Ayush Shrivastava United States	7	84 0.4×	97 0.9×	20 1.8×	4 0.5×	6 0.9×	12	158
Jiannan Wu Hong Kong	4	159 0.8×	95 0.9×	11 1.0×	5 0.6×	5 0.7×	5	225
Raphael Gontijo Lopes United States	3	179 0.9×	180 1.7×	18 1.6×	2 0.3×	4 0.6×	5	272
Yehao Li China	3	435 2.1×	218 2.0×	12 1.1×	4 0.5×	4 0.6×	3	464
Yuxiang Jia China	6	129 0.6×	81 0.8×	5 0.5×	13 1.6×	13 1.9×	26	218
Duzhen Zhang China	7	123 0.6×	149 1.4×	12 1.1×	4 0.5×	6 0.9×	17	227
Chelsea Voss Canada	6	55 0.3×	106 1.0×	8 0.7×	26 3.3×	4 0.6×	7	163

Countries citing papers authored by Matteo Stefanini

Since Specialization

Citations

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

Fields of papers citing papers by Matteo Stefanini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Stefanini

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Stefanini. A scholar is included among the top collaborators of Matteo Stefanini 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 Matteo Stefanini. Matteo Stefanini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Stefanini, Matteo, et al.. (2023). Predicting gene and protein expression levels from DNA and protein sequences with Perceiver. Computer Methods and Programs in Biomedicine. 234. 107504–107504. 6 indexed citations

2.

Messina, Nicola, Matteo Stefanini, Marcella Cornia, et al.. (2022). ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and Retrieval. Zenodo (CERN European Organization for Nuclear Research). 64–70. 11 indexed citations

3.

Stefanini, Matteo, Marcella Cornia, Lorenzo Baraldi, et al.. (2022). From Show to Tell: A Survey on Deep Learning-Based Image Captioning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 539–559. 198 indexed citations breakdown →

4.

Stefanini, Matteo, et al.. (2022). CaMEL: Mean Teacher Learning for Image Captioning. 2022 26th International Conference on Pattern Recognition (ICPR). 4087–4094. 18 indexed citations

5.

Stefanini, Matteo, Riccardo Lancellotti, Lorenzo Baraldi, & Simone Calderara. (2019). A Deep-learning-based approach to VM behavior Identification in Cloud Systems. IRIS UNIMORE (University of Modena and Reggio Emilia). 4 indexed citations

6.

Cornia, Marcella, Matteo Stefanini, Lorenzo Baraldi, Massimiliano Corsini, & Rita Cucchiara. (2019). Explaining digital humanities by aligning images and textual descriptions. Pattern Recognition Letters. 129. 166–172. 18 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.

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