Joan Serra-Sagristà

1.7k total citations
145 papers, 1.2k citations indexed

About

Joan Serra-Sagristà is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Joan Serra-Sagristà has authored 145 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Computer Vision and Pattern Recognition, 36 papers in Artificial Intelligence and 30 papers in Signal Processing. Recurrent topics in Joan Serra-Sagristà's work include Advanced Data Compression Techniques (115 papers), Image and Signal Denoising Methods (66 papers) and Algorithms and Data Compression (26 papers). Joan Serra-Sagristà is often cited by papers focused on Advanced Data Compression Techniques (115 papers), Image and Signal Denoising Methods (66 papers) and Algorithms and Data Compression (26 papers). Joan Serra-Sagristà collaborates with scholars based in Spain, United States and United Kingdom. Joan Serra-Sagristà's co-authors include Ian Blanes, Francesc Aulí-Llinàs, Joan Bartrina-Rapestà, Michael W. Marcellin, Miguel Hernández-Cabronero, Enrico Magli, Víctor Sánchez, Aaron Kiely, Valero Laparra and Gustau Camps‐Valls and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Joan Serra-Sagristà

136 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joan Serra-Sagristà Spain 20 1.0k 320 206 183 80 145 1.2k
J.F. Arnold Australia 17 846 0.8× 255 0.8× 504 2.4× 73 0.4× 129 1.6× 83 1.1k
S. Z. Li China 5 655 0.6× 198 0.6× 74 0.4× 210 1.1× 35 0.4× 8 993
P. Haavisto Finland 13 1.0k 1.0× 335 1.0× 403 2.0× 110 0.6× 32 0.4× 33 1.2k
D. Androutsos Canada 16 560 0.5× 225 0.7× 140 0.7× 100 0.5× 59 0.7× 43 767
Jarno Mielikäinen United States 18 1.2k 1.1× 175 0.5× 101 0.5× 149 0.8× 74 0.9× 56 1.6k
Donggyu Sim South Korea 17 924 0.9× 166 0.5× 438 2.1× 98 0.5× 24 0.3× 130 1.2k
Francisco Argüello Spain 16 285 0.3× 437 1.4× 117 0.6× 150 0.8× 83 1.0× 80 858
Qing Guo China 16 639 0.6× 268 0.8× 27 0.1× 206 1.1× 35 0.4× 58 896
Silvano Di Zenzo Italy 10 818 0.8× 273 0.9× 65 0.3× 117 0.6× 16 0.2× 18 1.1k
A. Agarwala United States 7 586 0.6× 127 0.4× 41 0.2× 104 0.6× 27 0.3× 7 755

Countries citing papers authored by Joan Serra-Sagristà

Since Specialization
Citations

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

Fields of papers citing papers by Joan Serra-Sagristà

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Serra-Sagristà. 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 Joan Serra-Sagristà. The network helps show where Joan Serra-Sagristà may publish in the future.

Co-authorship network of co-authors of Joan Serra-Sagristà

This figure shows the co-authorship network connecting the top 25 collaborators of Joan Serra-Sagristà. A scholar is included among the top collaborators of Joan Serra-Sagristà 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 Joan Serra-Sagristà. Joan Serra-Sagristà 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.
2.
Hadid, Abdenour, et al.. (2024). Deepfake Detection Using Spatiotemporal Transformer. ACM Transactions on Multimedia Computing Communications and Applications. 20(11). 1–21. 18 indexed citations
3.
Ballé, Johannes, et al.. (2023). A Scalable Reduced-Complexity Compression of Hyperspectral Remote Sensing Images Using Deep Learning. Remote Sensing. 15(18). 4422–4422. 6 indexed citations
4.
Hernández-Cabronero, Miguel, et al.. (2021). DivNet: Efficient Convolutional Neural Network via Multilevel Hierarchical Architecture Design. IEEE Access. 9. 105892–105901. 5 indexed citations
5.
Blanes, Ian, Miguel Hernández-Cabronero, Joan Serra-Sagristà, & Michael W. Marcellin. (2020). Redundancy and Optimization of tANS Entropy Encoders. IEEE Transactions on Multimedia. 23. 4341–4350. 2 indexed citations
6.
Serra-Sagristà, Joan, et al.. (2019). Regression Wavelet Analysis for Near-Lossless Remote Sensing Data Compression. IEEE Transactions on Geoscience and Remote Sensing. 58(2). 790–798. 12 indexed citations
7.
Blanes, Ian, Miguel Hernández-Cabronero, Joan Serra-Sagristà, & Michael W. Marcellin. (2019). Lower Bounds on the Redundancy of Huffman Codes With Known and Unknown Probabilities. IEEE Access. 7. 115857–115870. 3 indexed citations
8.
Martínez, Manuel & Joan Serra-Sagristà. (2019). Rice-Marlin Codes: Tiny and Efficient Variable-to-Fixed Codes. 596–596. 1 indexed citations
9.
Pinho, Armando J., et al.. (2019). Competitive Segmentation Performance on Near-Lossless and Lossy Compressed Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters. 17(5). 834–838. 4 indexed citations
10.
Martínez, Manuel, Monica Haurilet, Rainer Stiefelhagen, & Joan Serra-Sagristà. (2017). Marlin: A High Throughput Variable-to-Fixed Codec Using Plurally Parsable Dictionaries. Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona). abs 902 271. 161–170. 8 indexed citations
11.
Hernández-Cabronero, Miguel, Víctor Sánchez, Francesc Aulí-Llinàs, & Joan Serra-Sagristà. (2016). Fast MCT optimization for the compression of whole-slide images. 2370–2374. 4 indexed citations
12.
Sánchez, Víctor, Francesc Aulí-Llinàs, Joan Bartrina-Rapestà, & Joan Serra-Sagristà. (2014). Improvements to HEVC Intra Coding for Lossless Medical Image Compression. 423–423. 12 indexed citations
13.
Sánchez, Víctor, Francesc Aulí-Llinàs, Joan Bartrina-Rapestà, & Joan Serra-Sagristà. (2014). HEVC-based lossless compression of Whole Slide pathology images. 297–301. 20 indexed citations
14.
Hernández-Cabronero, Miguel, et al.. (2012). DNA Microarray Image Coding. 32–41. 4 indexed citations
15.
Blanes, Ian & Joan Serra-Sagristà. (2009). Clustered Reversible-KLT for Progressive Lossy-to-Lossless 3d Image Coding. 233–242. 16 indexed citations
16.
Serra-Sagristà, Joan, et al.. (2008). Encoding of images containing no-data regions within JPEG2000 framework. 2004. 1057–1060. 7 indexed citations
17.
Bartrina-Rapestà, Joan, Francesc Aulí-Llinàs, Joan Serra-Sagristà, et al.. (2007). Region of interest coding applied to map overlapping in Geographic Information Systems. 9. 5001–5004. 3 indexed citations
18.
Zabala, Alaitz, Xavier Pons, Joan Masó, et al.. (2005). Effects of JPEG2000 lossy compression on remote sensing image classification for mapping natural areas. Annual Conference on Computers. 93. 1 indexed citations
19.
Schönwälder, Jürgen, et al.. (2005). Ambient networks : 16th IFIP/IEEE International Workshop on Distributed Systems : Operations and Management, DSOM 2005, Barcelona, Spain, October 24-26, 2005 : proceedings. Springer eBooks. 1 indexed citations
20.
Minguillón, Julià, et al.. (2000). Influence Of Lossy Compression OnHyperspectral Image Classification Accuracy. WIT transactions on information and communication technologies. 25. 1 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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