Panagiotis Pintelas

6.5k total citations · 3 hit papers
96 papers, 4.1k citations indexed

About

Panagiotis Pintelas is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Numerical Analysis. According to data from OpenAlex, Panagiotis Pintelas has authored 96 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 13 papers in Numerical Analysis. Recurrent topics in Panagiotis Pintelas's work include Imbalanced Data Classification Techniques (13 papers), Machine Learning and Data Classification (13 papers) and Advanced Optimization Algorithms Research (13 papers). Panagiotis Pintelas is often cited by papers focused on Imbalanced Data Classification Techniques (13 papers), Machine Learning and Data Classification (13 papers) and Advanced Optimization Algorithms Research (13 papers). Panagiotis Pintelas collaborates with scholars based in Greece and India. Panagiotis Pintelas's co-authors include Sotiris Kotsiantis, Ioannis E. Livieris, Ioannis D. Zaharakis, Emmanuel Pintelas, Dimitris Kanellopoulos, Christos Pierrakeas, Stavros Stavroyiannis, Michalis Xenos, Andreas Kanavos and Theodore Kotsilieris and has published in prestigious journals such as Computers & Education, Sensors and Neurocomputing.

In The Last Decade

Panagiotis Pintelas

91 papers receiving 3.8k citations

Hit Papers

Machine learning: a review of classification and combinin... 2006 2026 2012 2019 2006 2020 2007 250 500 750 1000
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.

  1. Machine learning: a review of classification and combining techniques
    2006 1.0k citations Sotiris Kotsiantis, Panagiotis Pintelas et al. profile →
  2. A CNN–LSTM model for gold price time-series forecasting
    2020 547 citations Ioannis E. Livieris, Emmanuel Pintelas et al. Neural Computing and Applications profile →
  3. Data Preprocessing For Supervised Leaning
    2007 461 citations Sotiris Kotsiantis, Panagiotis Pintelas et al. profile →

Peers

Panagiotis Pintelas
Paulo Cortez Portugal
Jiuyong Li Australia
César Hervás‐Martínez Spain
Oded Maimon Israel
Aytuğ Onan Türkiye
Natalia Díaz-Rodríguez Spain
Chuen–Tsai Sun Taiwan
Senén Barro Spain
Sergio Gil-López Spain
Richard Benjamins Spain
Paulo Cortez Portugal
Panagiotis Pintelas
Citations per year, relative to Panagiotis Pintelas Panagiotis Pintelas (= 1×) peers Paulo Cortez

Countries citing papers authored by Panagiotis Pintelas

Since Specialization
Citations

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

Fields of papers citing papers by Panagiotis Pintelas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Panagiotis Pintelas

This figure shows the co-authorship network connecting the top 25 collaborators of Panagiotis Pintelas. A scholar is included among the top collaborators of Panagiotis Pintelas 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 Panagiotis Pintelas. Panagiotis Pintelas 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.
Pintelas, Emmanuel, Ioannis E. Livieris, & Panagiotis Pintelas. (2025). Quantization-Based 3D-CNNs Through Circular Gradual Unfreezing for DeepFake Detection. IEEE Transactions on Artificial Intelligence. 6(12). 3351–3363.
2.
Pintelas, Emmanuel, et al.. (2025). Feature augmentation-based CNN framework for skin-cancer diagnosis. Evolving Systems. 16(1). 1 indexed citations
3.
Pintelas, Emmanuel, Ioannis E. Livieris, & Panagiotis Pintelas. (2024). Adaptive augmentation framework for domain independent few shot learning. Knowledge-Based Systems. 299. 112047–112047. 4 indexed citations
4.
Pintelas, Emmanuel, et al.. (2024). MobileNet-HeX: Heterogeneous Ensemble of MobileNet eXperts for Efficient and Scalable Vision Model Optimization. Big Data and Cognitive Computing. 9(1). 2–2.
5.
Livieris, Ioannis E., et al.. (2024). Mutual information-based neighbor selection method for causal effect estimation. Neural Computing and Applications. 36(16). 9141–9155. 8 indexed citations
6.
Livieris, Ioannis E., et al.. (2023). Explainable Image Similarity: Integrating Siamese Networks and Grad-CAM. Journal of Imaging. 9(10). 224–224. 14 indexed citations
7.
Acharya, Biswaranjan, et al.. (2023). Heart Disease Prediction Using Concatenated Hybrid Ensemble Classifiers. Algorithms. 16(12). 538–538. 11 indexed citations
8.
Kanavos, Andreas, et al.. (2021). Employing Fuzzy Logic to Analyze the Structure of Complex Biological and Epidemic Spreading Models. Mathematics. 9(9). 977–977. 13 indexed citations
9.
Livieris, Ioannis E., Stavros Stavroyiannis, Lazaros Iliadis, & Panagiotis Pintelas. (2021). Smoothing and stationarity enforcement framework for deep learning time-series forecasting. Neural Computing and Applications. 33(20). 14021–14035. 24 indexed citations
10.
Apostolopoulos, Ioannis D., Emmanuel Pintelas, Ioannis E. Livieris, et al.. (2021). Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques. Medical & Biological Engineering & Computing. 59(6). 1299–1310. 26 indexed citations
11.
Livieris, Ioannis E. & Panagiotis Pintelas. (2019). An improved weight-constrained neural network training algorithm. Neural Computing and Applications. 32(9). 4177–4185. 12 indexed citations
12.
Livieris, Ioannis E., Andreas Kanavos, & Panagiotis Pintelas. (2019). Detecting Lung Abnormalities From X-rays Using an Improved SSL Algorithm. Electronic Notes in Theoretical Computer Science. 343. 19–33. 7 indexed citations
13.
Livieris, Ioannis E., Emmanuel Pintelas, & Panagiotis Pintelas. (2019). Gender Recognition by Voice Using an Improved Self-Labeled Algorithm. Machine Learning and Knowledge Extraction. 1(1). 492–503. 35 indexed citations
14.
Pintelas, Panagiotis. (2018). Predicting Protein Localization Sites Using an Ensemble Self-Labeled Framework. Biomedical Journal of Scientific & Technical Research. 11(2). 1 indexed citations
15.
Livieris, Ioannis E., et al.. (2018). A descent hybrid conjugate gradient method based on the memoryless BFGS update. Numerical Algorithms. 79(4). 1169–1185. 22 indexed citations
16.
Livieris, Ioannis E. & Panagiotis Pintelas. (2012). A new class of spectral conjugate gradient methods based on a modified secant equation for unconstrained optimization. Journal of Computational and Applied Mathematics. 239. 396–405. 21 indexed citations
17.
Livieris, Ioannis E. & Panagiotis Pintelas. (2012). Globally convergent modified Perry’s conjugate gradient method. Applied Mathematics and Computation. 218(18). 9197–9207. 24 indexed citations
18.
Pintelas, Panagiotis, et al.. (2010). A practical method for solving large-scale TRS. Optimization Letters. 5(2). 207–227. 5 indexed citations
19.
Pintelas, Panagiotis, et al.. (2008). Solving the quadratic trust-region subproblem in a low-memory BFGS framework. Optimization methods & software. 23(5). 651–674. 8 indexed citations
20.
Kotsiantis, Sotiris & Panagiotis Pintelas. (2003). Mixture of Expert Agents for Handling Imbalanced Data Sets. 66 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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