Michele Svanera

416 total citations
11 papers, 257 citations indexed

About

Michele Svanera is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Michele Svanera has authored 11 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Cognitive Neuroscience and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Michele Svanera's work include Neural dynamics and brain function (3 papers), Face Recognition and Perception (2 papers) and Visual Attention and Saliency Detection (2 papers). Michele Svanera is often cited by papers focused on Neural dynamics and brain function (3 papers), Face Recognition and Perception (2 papers) and Visual Attention and Saliency Detection (2 papers). Michele Svanera collaborates with scholars based in Italy, United Kingdom and Netherlands. Michele Svanera's co-authors include Sergio Benini, Pietro Poesio, Riccardo Leonardi, Lars Muckli, Nicola Adami, Dennis Bontempi, Gal Raz, Giancarlo Valente, Mattia Savardi and Rainer Goebel and has published in prestigious journals such as NeuroImage, Human Brain Mapping and Medical Image Analysis.

In The Last Decade

Michele Svanera

11 papers receiving 250 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michele Svanera Italy	8	104	69	64	63	36	11	257
Hadi Kalani Iran	12	192 1.8×	14 0.2×	21 0.3×	102 1.6×	8 0.2×	39	392
Nigel Smith Taiwan	10	49 0.5×	36 0.5×	18 0.3×	50 0.8×	54 1.5×	43	441
Jun Zhong China	10	196 1.9×	22 0.3×	13 0.2×	48 0.8×	24 0.7×	40	342
Alireza Rafiei Iran	9	35 0.3×	36 0.5×	10 0.2×	53 0.8×	4 0.1×	17	317
Hengyi Yang China	8	165 1.6×	4 0.1×	32 0.5×	70 1.1×	5 0.1×	13	263
Yutaka YOKOYAMA Japan	12	67 0.6×	17 0.2×	103 1.6×	45 0.7×	5 0.1×	103	401
Kai Ye China	10	47 0.5×	6 0.1×	8 0.1×	129 2.0×	49 1.4×	26	279
Shuhong Cheng China	8	17 0.2×	30 0.4×	104 1.6×	20 0.3×	5 0.1×	16	270
Djordje Mitrović United Kingdom	9	105 1.0×	41 0.6×	7 0.1×	19 0.3×	3 0.1×	15	224
Ziru Li China	9	23 0.2×	8 0.1×	20 0.3×	46 0.7×	95 2.6×	25	303

Countries citing papers authored by Michele Svanera

Since Specialization

Citations

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

Fields of papers citing papers by Michele Svanera

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Svanera

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

All Works

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11 of 11 papers shown

Svanera, Michele, Mattia Savardi, Alberto Signoroni, Sergio Benini, & Lars Muckli. (2024). Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site data. Medical Image Analysis. 93. 103090–103090. 4 indexed citations

Svanera, Michele, Sergio Benini, Dennis Bontempi, & Lars Muckli. (2021). CEREBRUM‐7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes. Human Brain Mapping. 42(17). 5563–5580. 15 indexed citations

Svanera, Michele, Andrew Morgan, Lucy S. Petro, & Lars Muckli. (2021). A self-supervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. Journal of Vision. 21(7). 5–5. 1 indexed citations

Svanera, Michele, Mattia Savardi, Sergio Benini, et al.. (2019). Transfer learning of deep neural network representations for fMRI decoding. Journal of Neuroscience Methods. 328. 108319–108319. 19 indexed citations

Raz, Gal, et al.. (2019). A Robust Neural Fingerprint of Cinematic Shot-Scale. Research Publications (Maastricht University). 13(3). 23–52. 5 indexed citations

Svanera, Michele, et al.. (2018). Hair detection, segmentation, and hairstyle classification in the wild. Image and Vision Computing. 71. 25–37. 26 indexed citations

Raz, Gal, Michele Svanera, Neomi Singer, et al.. (2017). Robust inter-subject audiovisual decoding in functional magnetic resonance imaging using high-dimensional regression. NeuroImage. 163. 244–263. 9 indexed citations

Benini, Sergio, et al.. (2016). Shot scale distribution in art films. Multimedia Tools and Applications. 75(23). 16499–16527. 15 indexed citations

Svanera, Michele, et al.. (2016). Figaro, hair detection and segmentation in the wild. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 933–937. 23 indexed citations

10.

Svanera, Michele, et al.. (2015). Size distribution and Sauter mean diameter of micro bubbles for a Venturi type bubble generator. Experimental Thermal and Fluid Science. 70. 51–60. 129 indexed citations

11.

Svanera, Michele, et al.. (2015). Over-the-shoulder shot detection in art films. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 33. 1–6. 11 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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