Anselmo Ferreira

1.2k total citations
20 papers, 875 citations indexed

About

Anselmo Ferreira is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Anselmo Ferreira has authored 20 papers receiving a total of 875 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Media Technology. Recurrent topics in Anselmo Ferreira's work include Digital Media Forensic Detection (9 papers), Advanced Steganography and Watermarking Techniques (6 papers) and Stock Market Forecasting Methods (3 papers). Anselmo Ferreira is often cited by papers focused on Digital Media Forensic Detection (9 papers), Advanced Steganography and Watermarking Techniques (6 papers) and Stock Market Forecasting Methods (3 papers). Anselmo Ferreira collaborates with scholars based in Brazil, Italy and China. Anselmo Ferreira's co-authors include Anderson Rocha, Diego Reforgiato Recupero, Salvatore Carta, Gilson A. Giraldi, Alessandro Sebastian Podda, Tiago Carvalho, Antonio Sanna, Bin Li, Jefersson A. dos Santos and Shunquan Tan and has published in prestigious journals such as IEEE Transactions on Image Processing, Expert Systems with Applications and IEEE Access.

In The Last Decade

Anselmo Ferreira

20 papers receiving 846 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anselmo Ferreira Brazil 12 494 172 158 151 93 20 875
Linkai Luo China 14 122 0.2× 39 0.2× 128 0.8× 164 1.1× 17 0.2× 40 610
Hubert Cardot France 11 210 0.4× 50 0.3× 54 0.3× 217 1.4× 43 0.5× 31 473
Chuin-Mu Wang Taiwan 11 174 0.4× 74 0.4× 84 0.5× 162 1.1× 5 0.1× 41 510
Zhengkai Liu China 13 290 0.6× 55 0.3× 58 0.4× 74 0.5× 3 0.0× 57 610
Ying Han Pang Malaysia 16 450 0.9× 84 0.5× 55 0.3× 222 1.5× 4 0.0× 90 842
Ashraful Islam Bangladesh 12 504 1.0× 105 0.6× 7 0.0× 227 1.5× 19 0.2× 77 999
Xingyu Zhou China 12 98 0.2× 13 0.1× 137 0.9× 150 1.0× 7 0.1× 70 563
Milan Parmar China 9 147 0.3× 29 0.2× 40 0.3× 183 1.2× 10 0.1× 15 491
G. Maragatham India 9 107 0.2× 36 0.2× 28 0.2× 166 1.1× 10 0.1× 39 614
Pundru Chandra Shaker Reddy India 23 113 0.2× 24 0.1× 79 0.5× 421 2.8× 20 0.2× 93 1.1k

Countries citing papers authored by Anselmo Ferreira

Since Specialization
Citations

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

Fields of papers citing papers by Anselmo Ferreira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anselmo Ferreira

This figure shows the co-authorship network connecting the top 25 collaborators of Anselmo Ferreira. A scholar is included among the top collaborators of Anselmo Ferreira 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 Anselmo Ferreira. Anselmo Ferreira 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.
Carta, Salvatore, Anselmo Ferreira, Diego Reforgiato Recupero, & Roberto Saia. (2021). Credit scoring by leveraging an ensemble stochastic criterion in a transformed feature space. Progress in Artificial Intelligence. 10(4). 417–432. 10 indexed citations
2.
Ferreira, Anselmo, Ehsan Nowroozi, & Mauro Barni. (2021). VIPPrint: Validating Synthetic Image Detection and Source Linking Methods on a Large Scale Dataset of Printed Documents. Journal of Imaging. 7(3). 50–50. 11 indexed citations
3.
Ferreira, Anselmo, et al.. (2021). Ensembling Shallow Siamese Neural Network Architectures for Printed Documents Verification in Data-Scarcity Scenarios. IEEE Access. 9. 133924–133939. 4 indexed citations
4.
Carta, Salvatore, et al.. (2020). A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning. Applied Intelligence. 51(2). 889–905. 90 indexed citations
5.
Carta, Salvatore, Anselmo Ferreira, Alessandro Sebastian Podda, Diego Reforgiato Recupero, & Antonio Sanna. (2020). Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting. Expert Systems with Applications. 164. 113820–113820. 143 indexed citations
6.
Carta, Salvatore, et al.. (2019). A Holistic Auto-Configurable Ensemble Machine Learning Strategy for Financial Trading. Computation. 7(4). 67–67. 10 indexed citations
7.
Chen, Changsheng, et al.. (2019). A Copy-Proof Scheme Based on the Spectral and Spatial Barcoding Channel Models. IEEE Transactions on Information Forensics and Security. 15. 1056–1071. 16 indexed citations
8.
Ferreira, Anselmo, et al.. (2019). Eyes in the Skies: A Data-Driven Fusion Approach to Identifying Drug Crops From Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(12). 4773–4786. 12 indexed citations
9.
Carta, Salvatore, et al.. (2019). A combined entropy-based approach for a proactive credit scoring. Engineering Applications of Artificial Intelligence. 87. 103292–103292. 26 indexed citations
10.
Li, Bin, et al.. (2018). ReST-Net: Diverse Activation Modules and Parallel Subnets-Based CNN for Spatial Image Steganalysis. IEEE Signal Processing Letters. 25(5). 650–654. 84 indexed citations
11.
Ferreira, Anselmo, Han Chen, Bin Li, & Jiwu Huang. (2018). An Inception-Based Data-Driven Ensemble Approach to Camera Model Identification. abs 1703 4856. 1–7. 8 indexed citations
12.
Ferreira, Anselmo & Gilson A. Giraldi. (2017). Convolutional Neural Network approaches to granite tiles classification. Expert Systems with Applications. 84. 1–11. 107 indexed citations
13.
Ferreira, Anselmo, Luca Bondi, Luca Baroffio, et al.. (2017). Data-Driven Feature Characterization Techniques for Laser Printer Attribution. IEEE Transactions on Information Forensics and Security. 12(8). 1860–1873. 41 indexed citations
14.
Ferreira, Anselmo, et al.. (2016). Behavior Knowledge Space-Based Fusion for Copy–Move Forgery Detection. IEEE Transactions on Image Processing. 25(10). 4729–4742. 50 indexed citations
15.
Ferreira, Anselmo, Jefersson A. dos Santos, & Anderson Rocha. (2016). Multi-directional and multi-scale perturbation approaches for blind forensic median filtering detection. Intelligent Data Analysis. 20(s1). S17–S36. 1 indexed citations
16.
Carvalho, Tiago, et al.. (2015). Going deeper into copy-move forgery detection: Exploring image telltales via multi-scale analysis and voting processes. Journal of Visual Communication and Image Representation. 29. 16–32. 169 indexed citations
17.
Ferreira, Anselmo, et al.. (2014). Laser printer attribution: Exploring new features and beyond. Forensic Science International. 247. 105–125. 48 indexed citations
18.
Ferreira, Anselmo, et al.. (2013). A multiple camera methodology for automatic localization and tracking of futsal players. Pattern Recognition Letters. 39. 21–30. 27 indexed citations
19.
Goldenstein, Siome, et al.. (2012). Automatic Tracking of Indoor Soccer Players Using Videos from Multiple Cameras. 1. 174–181. 9 indexed citations
20.
Ferreira, Anselmo, et al.. (2010). Image Segmentation Using Component Tree and Normalized Cut. 1. 317–322. 9 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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