Marco Grangetto
About
In The Last Decade
Marco Grangetto
141 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 97
- Computer Vision and Pattern Recognition 1.1k
- Computer Networks and Communications 672
- Signal Processing 533
- Electrical and Electronic Engineering 463
- Artificial Intelligence 398
Countries citing papers authored by Marco Grangetto
This map shows the geographic impact of Marco Grangetto'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 Marco Grangetto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Grangetto more than expected).
Fields of papers citing papers by Marco Grangetto
This network shows the impact of papers produced by Marco Grangetto. 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 Marco Grangetto. The network helps show where Marco Grangetto may publish in the future.
Co-authorship network of co-authors of Marco Grangetto
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Grangetto. A scholar is included among the top collaborators of Marco Grangetto 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 Marco Grangetto. Marco Grangetto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | AI-Assisted Diagnosis for Covid-19 CXR Screening: from Data Collection to Clinical Validation | Marco Grosso, Marco Busso et al. | 0 | |
| 2 | COVID-19 Infection Percentage Estimation from Computed Tomography Scans: Results and Insights from the International Per-COVID-19 Challenge | Sensors | Fares Bougourzi, Cosimo Distante et al. | 1 |
| 3 | A lightweight deep learning architecture for malaria parasite-type classification and life cycle stage detection | Neural Computing and Applications | Muhammad Shahid Farid, Attilio Fiandrotti et al. | 8 |
| 4 | Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke | Frontiers in Neuroinformatics | Federico D’Agata, Enzo Tartaglione et al. | 7 |
| 5 | On the robustness of three classes of rateless codes against pollution attacks in P2P networks | Peer-to-Peer Networking and Applications | Rossano Gaeta, Marco Grangetto | 0 |
| 6 | HEMP: High-order entropy minimization for neural network compression | Neurocomputing | Enzo Tartaglione, Stéphane Lathuilière et al. | 4 |
| 7 | Robust gait identification using Kinect dynamic skeleton data | Multimedia Tools and Applications | Marco Grangetto et al. | 17 |
| 8 | Detection and Tracking of Astral Microtubules in Fluorescence Microscopy Images | Institutional Research Information System University of Turin (University of Turin) | Joshua A. Levine, Marco Grangetto et al. | 2 |
| 9 | Perceptual quality assessment of 3D synthesized images | Institutional Research Information System University of Turin (University of Turin) | Muhammad Shahid Farid, Maurizio Lucenteforte et al. | 20 |
| 10 | DOST: a distributed object segmentation tool | Multimedia Tools and Applications | Muhammad Shahid Farid, Maurizio Lucenteforte et al. | 15 |
| 11 | Depth image based rendering with inverse mapping | Institutional Research Information System University of Turin (University of Turin) | Muhammad Shahid Farid, Maurizio Lucenteforte et al. | 24 |
| 12 | A high capacity reversible data hiding scheme for radiographic images | Institutional Research Information System University of Turin (University of Turin) | Davide Cavagnino, Marco Grangetto et al. | 1 |
| 13 | Sliding-Window Raptor Codes for Efficient Scalable Wireless Video Broadcasting With Unequal Loss Protection | IEEE Transactions on Image Processing | Pasquale Cataldi, Marco Grangetto et al. | 53 |
| 14 | Redundant Slice Optimal Allocation for H.264 Multiple Description Coding | IEEE Transactions on Circuits and Systems for Video Technology | Tammam Tillo, Marco Grangetto et al. | 71 |
| 15 | Iterative Decoding of Serially Concatenated Arithmetic and Channel Codes With JPEG 2000 Applications | IEEE Transactions on Image Processing | Marco Grangetto, Gabriella Olmo et al. | 20 |
| 16 | Distributed Arithmetic Coding | IEEE Communications Letters | Marco Grangetto, Enrico Magli et al. | 37 |
| 17 | Implementation and Performance Evaluation of LT and Raptor Codes for Multimedia Applications | Pasquale Cataldi, Marco Grangetto et al. | 34 | |
| 18 | A syntax-preserving error resilience tool for JPEG 2000 based on error correcting arithmetic coding | IEEE Transactions on Image Processing | Marco Grangetto, Enrico Magli et al. | 13 |
| 19 | Ensuring quality of service for image transmission: hybrid loss protection | IEEE Transactions on Image Processing | Marco Grangetto, Enrico Magli et al. | 8 |
| 20 | Optimization and implementation of the integer wavelet transform for image coding | IEEE Transactions on Image Processing | Marco Grangetto, Enrico Magli et al. | 56 |
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.