Andrea Loddo

1.2k total citations
39 papers, 622 citations indexed

About

Andrea Loddo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics. According to data from OpenAlex, Andrea Loddo has authored 39 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 8 papers in Biophysics. Recurrent topics in Andrea Loddo's work include Digital Imaging for Blood Diseases (16 papers), AI in cancer detection (9 papers) and Cell Image Analysis Techniques (8 papers). Andrea Loddo is often cited by papers focused on Digital Imaging for Blood Diseases (16 papers), AI in cancer detection (9 papers) and Cell Image Analysis Techniques (8 papers). Andrea Loddo collaborates with scholars based in Italy, Brazil and Switzerland. Andrea Loddo's co-authors include Cecilia Di Ruberto, Lorenzo Putzu, M. Loddo, Michel Kocher, Giovanni Puglisi, Massimo Bartoletti, Stefano Lande, Livio Pompianu, Andrea Manconi and Giuliano Armano and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Andrea Loddo

32 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrea Loddo Italy 13 287 176 169 142 72 39 622
Mahesh Gour India 9 168 0.6× 272 1.5× 395 2.3× 246 1.7× 26 0.4× 11 801
Jatinder Manhas India 12 69 0.2× 186 1.1× 66 0.4× 103 0.7× 42 0.6× 32 475
Jagadeesh Pujari India 14 311 1.1× 65 0.4× 348 2.1× 38 0.3× 89 1.2× 53 753
Karim Gasmi Saudi Arabia 11 92 0.3× 119 0.7× 74 0.4× 72 0.5× 14 0.2× 34 345
Vandana Bharti India 9 82 0.3× 153 0.9× 154 0.9× 85 0.6× 20 0.3× 22 450
Md Jahid Hasan Bangladesh 11 45 0.2× 83 0.5× 280 1.7× 46 0.3× 36 0.5× 32 534
Muskan Goyal India 2 132 0.5× 341 1.9× 223 1.3× 394 2.8× 17 0.2× 6 777
Shoffan Saifullah Indonesia 14 109 0.4× 185 1.1× 63 0.4× 46 0.3× 12 0.2× 70 509
Samreen Naeem Pakistan 10 39 0.1× 93 0.5× 130 0.8× 95 0.7× 10 0.1× 26 434
Wataru Shimoda Japan 10 267 0.9× 169 1.0× 15 0.1× 62 0.4× 20 0.3× 28 480

Countries citing papers authored by Andrea Loddo

Since Specialization
Citations

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

Fields of papers citing papers by Andrea Loddo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Loddo

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

All Works

20 of 20 papers shown
1.
Loddo, Andrea, et al.. (2025). Advancements in radiomics: A comprehensive survey of feature types and their correlation on modalities and regions. Neurocomputing. 656. 131192–131192. 1 indexed citations
2.
Putzu, Lorenzo, Simone Porcu, & Andrea Loddo. (2025). Distributed collaborative machine learning in real-world application scenario: A white blood cell subtypes classification case study. Image and Vision Computing. 162. 105673–105673.
3.
Loddo, Andrea, et al.. (2025). A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario. Computers in Biology and Medicine. 186. 109704–109704. 2 indexed citations
4.
Loddo, Andrea, et al.. (2025). Is it fake or not? A comprehensive approach for multimodal fake news detection. UNICA IRIS Institutional Research Information System (University of Cagliari). 47. 100314–100314.
5.
Loddo, Andrea, et al.. (2025). Radio DINO: A foundation model for advanced radiomics and AI-driven medical imaging analysis. Computers in Biology and Medicine. 195. 110583–110583. 1 indexed citations
6.
Loddo, Andrea, et al.. (2024). Snarci at SemEval-2024 Task 4: Themis Model for Binary Classification of Memes. UNICA IRIS Institutional Research Information System (University of Cagliari). 853–858. 1 indexed citations
7.
Loddo, Andrea, Cecilia Di Ruberto, Giuliano Armano, & Andrea Manconi. (2024). Detecting coagulation time in cheese making by means of computer vision and machine learning techniques. Computers in Industry. 164. 104173–104173. 8 indexed citations
8.
Loddo, Andrea, et al.. (2024). Insights into radiomics: impact of feature selection and classification. Multimedia Tools and Applications. 84(26). 31695–31721. 11 indexed citations
9.
Loddo, Andrea, et al.. (2024). An Anomaly Detection Approach to Determine Optimal Cutting Time in Cheese Formation. Information. 15(6). 360–360. 1 indexed citations
10.
Loddo, Andrea, et al.. (2024). Understanding cheese ripeness: An artificial intelligence-based approach for hierarchical classification. Knowledge-Based Systems. 295. 111833–111833. 7 indexed citations
11.
Loddo, Andrea, et al.. (2024). Gastric Cancer Image Classification: A Comparative Analysis and Feature Fusion Strategies. Journal of Imaging. 10(8). 195–195. 6 indexed citations
12.
Loddo, Andrea, et al.. (2023). YOLO-PAM: Parasite-Attention-Based Model for Efficient Malaria Detection. Journal of Imaging. 9(12). 266–266. 9 indexed citations
13.
Ruberto, Cecilia Di, Andrea Loddo, & Lorenzo Putzu. (2023). On The Potential of Image Moments for Medical Diagnosis. Journal of Imaging. 9(3). 70–70. 3 indexed citations
14.
Loddo, Andrea, et al.. (2022). An effective and friendly tool for seed image analysis. UNICA IRIS Institutional Research Information System (University of Cagliari). 17 indexed citations
15.
Loddo, Andrea, et al.. (2021). Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method. Computers in Biology and Medicine. 141. 105032–105032. 101 indexed citations
16.
Bartoletti, Massimo, et al.. (2021). Cryptocurrency Scams: Analysis and Perspectives. IEEE Access. 9. 148353–148373. 43 indexed citations
17.
Loddo, Andrea, et al.. (2021). Deep Learning for COVID-19 Diagnosis from CT Images. Applied Sciences. 11(17). 8227–8227. 23 indexed citations
18.
Ruberto, Cecilia Di, Andrea Loddo, & Lorenzo Putzu. (2019). Detection of red and white blood cells from microscopic blood images using a region proposal approach. Computers in Biology and Medicine. 116. 103530–103530. 57 indexed citations
19.
Porcu, Simone, Andrea Loddo, Lorenzo Putzu, & Cecilia Di Ruberto. (2018). White Blood Cells Counting Via Vector Field Convolution Nuclei Segmentation. UNICA IRIS Institutional Research Information System (University of Cagliari). 5 indexed citations
20.
Loddo, Andrea, Lorenzo Putzu, Cecilia Di Ruberto, & Gianni Fenu. (2016). A Computer-Aided System for Differential Count from Peripheral Blood Cell Images. UNICA IRIS Institutional Research Information System (University of Cagliari). 112–118. 12 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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