Antonio Robles‐Kelly

4.2k total citations · 1 hit paper
146 papers, 2.5k citations indexed

About

Antonio Robles‐Kelly is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Antonio Robles‐Kelly has authored 146 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 104 papers in Computer Vision and Pattern Recognition, 31 papers in Media Technology and 30 papers in Artificial Intelligence. Recurrent topics in Antonio Robles‐Kelly's work include Advanced Vision and Imaging (30 papers), Computer Graphics and Visualization Techniques (26 papers) and Color Science and Applications (25 papers). Antonio Robles‐Kelly is often cited by papers focused on Advanced Vision and Imaging (30 papers), Computer Graphics and Visualization Techniques (26 papers) and Color Science and Applications (25 papers). Antonio Robles‐Kelly collaborates with scholars based in Australia, United Kingdom and China. Antonio Robles‐Kelly's co-authors include Edwin R. Hancock, Jun Zhou, Sen Jia, Yuntao Qian, Zhouyu Fu, Tariq M. Khan, Cong Phuoc Huynh, Mengmeng Ge, Zubair Baig and Xiping Fu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Antonio Robles‐Kelly

137 papers receiving 2.4k citations

Hit Papers

Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained... 2011 2026 2016 2021 2011 100 200 300 400
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. Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained Nonnegative Matrix Factorization
    2011 453 citations Jun Zhou, Antonio Robles‐Kelly et al. profile →

Peers

Antonio Robles‐Kelly
Xianming Liu China
Zhenkuan Pan China
Georgios Tziritas Greece
Guowei Yang China
A. Khotanzad United States
Zongben Xu China
Feilong Cao China
Byeungwoo Jeon South Korea
Thrasyvoulos N. Pappas United States
Xianming Liu China
Antonio Robles‐Kelly
Citations per year, relative to Antonio Robles‐Kelly Antonio Robles‐Kelly (= 1×) peers Xianming Liu

Countries citing papers authored by Antonio Robles‐Kelly

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Robles‐Kelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antonio Robles‐Kelly. 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 Antonio Robles‐Kelly. The network helps show where Antonio Robles‐Kelly may publish in the future.

Co-authorship network of co-authors of Antonio Robles‐Kelly

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Robles‐Kelly. A scholar is included among the top collaborators of Antonio Robles‐Kelly 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 Antonio Robles‐Kelly. Antonio Robles‐Kelly 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.
Luo, Wei, et al.. (2025). Taxonomy-guided routing in capsule network for hierarchical image classification. Knowledge-Based Systems. 329. 114444–114444.
2.
Robles‐Kelly, Antonio, et al.. (2024). Scene-cGAN: A GAN for underwater restoration and scene depth estimation. Computer Vision and Image Understanding. 250. 104225–104225. 2 indexed citations
3.
4.
Robles‐Kelly, Antonio, et al.. (2024). A consistency-aware deep capsule network for hierarchical multi-label image classification. Neurocomputing. 604. 128376–128376. 2 indexed citations
5.
Zhu, Ye, et al.. (2024). Point Cloud Normal Estimation via Representation Learning on Height Maps. UWA Profiles and Research Repository (UWA). 1–7.
6.
Luo, Wei, et al.. (2023). Robust federated learning under statistical heterogeneity via Hessian spectral decomposition. Pattern Recognition. 141. 109635–109635. 6 indexed citations
7.
Robles‐Kelly, Antonio, et al.. (2023). H-CapsNet: A capsule network for hierarchical image classification. Pattern Recognition. 147. 110135–110135. 8 indexed citations
8.
Lu, Xuequan, et al.. (2023). Contrastive Learning for Joint Normal Estimation and Point Cloud Filtering. IEEE Transactions on Visualization and Computer Graphics. 30(8). 4527–4541. 14 indexed citations
9.
Lu, Xuequan, et al.. (2023). Graph classification via discriminative edge feature learning. Pattern Recognition. 143. 109799–109799. 9 indexed citations
10.
Bouadjenek, Mohamed Reda, et al.. (2023). PERCY: A post-hoc explanation-based score for logic rule dissemination consistency assessment in sentiment classification. Knowledge-Based Systems. 275. 110685–110685. 1 indexed citations
11.
Tay, D.B.H., et al.. (2023). Deterministic sampling in heterogeneous graph neural networks. Pattern Recognition Letters. 172. 74–81. 4 indexed citations
12.
Robles‐Kelly, Antonio, et al.. (2023). Bio-Inspired Dual-Network Model to Tackle Statistical Heterogeneity in Federated Learning. 1 indexed citations
13.
Luo, Wei, et al.. (2023). Robust federated learning under statistical heterogeneity via hessian-weighted aggregation. Machine Learning. 112(2). 633–654. 15 indexed citations
14.
Khan, Tariq M., Syed S. Naqvi, Antonio Robles‐Kelly, & Imran Razzak. (2023). Retinal vessel segmentation via a Multi-resolution Contextual Network and adversarial learning. Neural Networks. 165. 310–320. 21 indexed citations
15.
Robles‐Kelly, Antonio, et al.. (2023). DGD-cGAN: A dual generator for image dewatering and restoration. Pattern Recognition. 148. 110159–110159. 19 indexed citations
16.
Zhu, Hao, Xiaoming Sun, Qi Zhang, et al.. (2019). Full View Optical Flow Estimation Leveraged From Light Field Superpixel. IEEE Transactions on Computational Imaging. 6. 12–23. 7 indexed citations
17.
Gu, Lin & Antonio Robles‐Kelly. (2012). Shadow detection via Rayleigh scattering and Mie theory. Own your potential (DEAKIN). 2 indexed citations
18.
Fu, Zhouyu, Antonio Robles‐Kelly, & Jun Zhou. (2010). MILIS: Multiple Instance Learning with Instance Selection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 33(5). 958–977. 126 indexed citations
19.
Robles‐Kelly, Antonio & Edwin R. Hancock. (2004). A Graph-Spectral Approach to Shape-From-Shading. IEEE Transactions on Image Processing. 13(7). 912–926. 14 indexed citations
20.
Robles‐Kelly, Antonio & Edwin R. Hancock. (2003). Edit Distance From Graph Spectra. Own your potential (DEAKIN). 234–241. 22 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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