Ismael Serrano

3.6k total citations
14 papers, 282 citations indexed

About

Ismael Serrano is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Industrial and Manufacturing Engineering. According to data from OpenAlex, Ismael Serrano has authored 14 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Industrial and Manufacturing Engineering. Recurrent topics in Ismael Serrano's work include Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Video Surveillance and Tracking Methods (4 papers). Ismael Serrano is often cited by papers focused on Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Video Surveillance and Tracking Methods (4 papers). Ismael Serrano collaborates with scholars based in Spain and United Kingdom. Ismael Serrano's co-authors include Óscar Déniz, Gloria Bueno, Tae‐Kyun Kim, José Luís Espinosa-Aranda, Íñigo Barandiarán, Guillermo Garcia-Hernando, Hugo Álvarez, A. Lázaro, Jairo R. Sánchez and M. Milagro Fernández-Carrobles and has published in prestigious journals such as IEEE Transactions on Image Processing, Sensors and Actuators A Physical and Applied Sciences.

In The Last Decade

Ismael Serrano

14 papers receiving 271 citations

Peers

Ismael Serrano

CVPR

AI

HI

IME

CNC

Ye Zheng China

Oliver Zendel Austria

Markus Murschitz Austria

Chandrashekar M Patil India

Arthur Bucker United Kingdom

G. Sreenu India

Hengduo Li United States

S Sanjana Bangladesh

Haochen Shi China

Ye Zheng China

Ismael Serrano

92 ×0.4

CVPR

89 ×0.4

AI

36 ×1.5

HI

34 ×1.5

IME

10 ×0.5

CNC

Citations per year, relative to Ismael Serrano Ismael Serrano (= 1×) peers Ye Zheng

Countries citing papers authored by Ismael Serrano

Since Specialization

Citations

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

Fields of papers citing papers by Ismael Serrano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ismael Serrano

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

All Works

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14 of 14 papers shown

1.

Álvarez, Hugo, et al.. (2020). Projection-Based Augmented Reality Assistance for Manual Electronic Component Assembly Processes. Applied Sciences. 10(3). 796–796. 33 indexed citations

2.

Serrano, Ismael, et al.. (2018). A Robust and Fast Deep Learning-Based Method for Defect Classification in Steel Surfaces. 455–460. 11 indexed citations

3.

Serrano, Ismael. (2018). Contributions to the Problem of Fight Detection in Video. ELCVIA Electronic Letters on Computer Vision and Image Analysis. 16(2). 33–36. 1 indexed citations

4.

Serrano, Ismael, Óscar Déniz, José Luís Espinosa-Aranda, & Gloria Bueno. (2018). Fight Recognition in Video Using Hough Forests and 2D Convolutional Neural Network. IEEE Transactions on Image Processing. 27(10). 4787–4797. 94 indexed citations

5.

Serrano, Ismael, Óscar Déniz, Gloria Bueno, Guillermo Garcia-Hernando, & Tae‐Kyun Kim. (2017). Spatio-temporal elastic cuboid trajectories for efficient fight recognition using Hough forests. Machine Vision and Applications. 29(2). 207–217. 19 indexed citations

6.

Fernández-Carrobles, M. Milagro, Ismael Serrano, Gloria Bueno, & Óscar Déniz. (2016). Bagging Tree Classifier and Texture Features for Tumor Identification in Histological Images. Procedia Computer Science. 90. 99–106. 12 indexed citations

7.

Garcia-Hernando, Guillermo, Hyung Jin Chang, Ismael Serrano, Óscar Déniz, & Tae‐Kyun Kim. (2016). Transition Hough forest for trajectory-based action recognition. University of Birmingham Research Portal (University of Birmingham). 1–8. 5 indexed citations

8.

Déniz, Óscar, Ismael Serrano, Gloria Bueno, & Tae‐Kyun Kim. (2015). Fast violence detection in video. 2. 478–485. 1 indexed citations

9.

Déniz, Óscar, Ismael Serrano, Gloria Bueno, & Tae‐Kyun Kim. (2014). Fast Violence Detection in Video. 83 indexed citations

10.

Serrano, Ismael, Óscar Déniz, & Gloria Bueno. (2013). VISILAB at MediaEval 2013: Fight Detection.. MediaEval. 5 indexed citations

11.

Lázaro, A., et al.. (2002). Ultrasonic sensing classification of foundry pieces applying neural networks. 653–658. 4 indexed citations

12.

Serrano, Ismael, et al.. (2002). A new method for object identification in ultrasonic systems using neural nets. 152–157. 10 indexed citations

13.

Serrano, Ismael, et al.. (1999). Ultrasonic inspection of foundry pieces applying wavelet transform analysis. 1. 375–380. 2 indexed citations

14.

Lázaro, A., et al.. (1999). Ultrasonic circular inspection for object recognition with sensor-robot integration. Sensors and Actuators A Physical. 77(1). 1–8. 2 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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