Benny Lövström

783 total citations
19 papers, 562 citations indexed

About

Benny Lövström is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computational Mechanics. According to data from OpenAlex, Benny Lövström has authored 19 papers receiving a total of 562 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 11 papers in Signal Processing and 3 papers in Computational Mechanics. Recurrent topics in Benny Lövström's work include Image and Video Quality Assessment (12 papers), Video Coding and Compression Technologies (8 papers) and Advanced Data Compression Techniques (7 papers). Benny Lövström is often cited by papers focused on Image and Video Quality Assessment (12 papers), Video Coding and Compression Technologies (8 papers) and Advanced Data Compression Techniques (7 papers). Benny Lövström collaborates with scholars based in Sweden, Spain and Greece. Benny Lövström's co-authors include Farook Sattar, G. Salomonsson, Muhammad Shahid, Hans‐Jürgen Zepernick, Muhammad Arslan Usman, Soo Young Shin, Lisimachos P. Kondi, Muhammad Gufran Khan, Begonya García-Zapirain and Kjell Brunnström and has published in prestigious journals such as IEEE Transactions on Image Processing, Journal of Electronic Imaging and EURASIP Journal on Image and Video Processing.

In The Last Decade

Benny Lövström

18 papers receiving 529 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benny Lövström Sweden 9 481 229 100 63 47 19 562
Zhangkai Ni China 15 713 1.5× 232 1.0× 75 0.8× 47 0.7× 28 0.6× 33 811
G. Bozdagi United States 9 370 0.8× 76 0.3× 64 0.6× 43 0.7× 68 1.4× 19 424
Ehsan Nadernejad Denmark 11 332 0.7× 119 0.5× 36 0.4× 24 0.4× 21 0.4× 34 423
Marina Nicolas France 2 321 0.7× 141 0.6× 32 0.3× 43 0.7× 71 1.5× 9 452
Chong Mou China 9 506 1.1× 89 0.4× 40 0.4× 83 1.3× 34 0.7× 18 676
Hojatollah Yeganeh Canada 12 1.2k 2.5× 628 2.7× 65 0.7× 81 1.3× 15 0.3× 24 1.3k
T. Vlachos United Kingdom 14 462 1.0× 170 0.7× 84 0.8× 18 0.3× 7 0.1× 40 532
Praful Gupta United States 8 418 0.9× 193 0.8× 43 0.4× 19 0.3× 19 0.4× 15 469
Claude Knaus Switzerland 10 558 1.2× 197 0.9× 14 0.1× 29 0.5× 32 0.7× 12 620
A.J. Patti United States 11 761 1.6× 391 1.7× 51 0.5× 21 0.3× 22 0.5× 24 844

Countries citing papers authored by Benny Lövström

Since Specialization
Citations

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

Fields of papers citing papers by Benny Lövström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benny Lövström

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

All Works

19 of 19 papers shown
1.
Holmgren, Johan, et al.. (2023). A Median-Based Misery Index for Travel Time Reliability. Procedia Computer Science. 220. 162–169. 2 indexed citations
2.
Khan, Muhammad Gufran, et al.. (2022). Reduced reference image and video quality assessments: review of methods. EURASIP Journal on Image and Video Processing. 2022(1). 14 indexed citations
3.
Dahl, Mattias, et al.. (2022). Modeling of road traffic flows in the neighboring regions. Procedia Computer Science. 198. 43–50. 1 indexed citations
4.
Usman, Muhammad Arslan, Soo Young Shin, Muhammad Shahid, & Benny Lövström. (2016). A No Reference Video Quality Metric Based on Jerkiness Estimation Focusing on Multiple Frame Freezing in Video Streaming. IETE Technical Review. 34(3). 309–320. 25 indexed citations
5.
Shahid, Muhammad, et al.. (2016). QoE rating performance evaluation of ITU-T recommended video quality metrics in the context of video freezes. Australian Journal of Electrical & Electronics Engineering. 13(2). 122–131. 2 indexed citations
6.
Shahid, Muhammad, et al.. (2016). Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models. Journal of Electronic Imaging. 25(5). 53012–53012. 4 indexed citations
7.
Shahid, Muhammad, et al.. (2015). A no-reference bitstream-based perceptual model for video quality estimation of videos affected by coding artifacts and packet losses. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9394. 93941F–93941F. 15 indexed citations
8.
Shahid, Muhammad, et al.. (2014). Analysis of the impact of temporal, spatial, and quantization variations on perceptual video quality. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1–5. 8 indexed citations
9.
Shahid, Muhammad, et al.. (2014). No-reference image and video quality assessment: a classification and review of recent approaches. EURASIP Journal on Image and Video Processing. 2014(1). 123 indexed citations
10.
Shahid, Muhammad, et al.. (2014). Effect of content characteristics on quality of experience of adaptive streaming. KTH Publication Database DiVA (KTH Royal Institute of Technology). 63–64. 5 indexed citations
11.
12.
Shahid, Muhammad, et al.. (2013). A no-reference machine learning based video quality predictor. KTH Publication Database DiVA (KTH Royal Institute of Technology). 446. 176–181. 19 indexed citations
13.
García-Zapirain, Begonya, et al.. (2013). Subband modulator Kalman filtering for single channel speech enhancement. KTH Publication Database DiVA (KTH Royal Institute of Technology). 5. 7442–7446. 8 indexed citations
14.
Shahid, Muhammad, et al.. (2012). Modulation frequency domain adaptive gain equalizer using convex optimization. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1–5. 2 indexed citations
15.
Shahid, Muhammad, et al.. (2011). A high quality adjustable complexity motion estimation algorithm for video encoders. 2. 507–511. 1 indexed citations
16.
Shahid, Muhammad, et al.. (2011). Modulation Domain Adaptive Gain Equalizer for Speech Enhancement. 6 indexed citations
17.
Shahid, Muhammad, et al.. (2011). A reduced complexity no-reference artificial neural network based video quality predictor. 5769. 517–521. 19 indexed citations
18.
Lövström, Benny, et al.. (2008). A NEW VIDEO QUALITY PREDICTOR BASED ON DECODER PARAMETER EXTRACTION. KTH Publication Database DiVA (KTH Royal Institute of Technology). 285–290. 6 indexed citations
19.
Sattar, Farook, et al.. (1997). Image enhancement based on a nonlinear multiscale method. IEEE Transactions on Image Processing. 6(6). 888–895. 297 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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