Mattias O’Nils

1.3k total citations
146 papers, 899 citations indexed

About

Mattias O’Nils is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Mattias O’Nils has authored 146 papers receiving a total of 899 indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Electrical and Electronic Engineering, 48 papers in Computer Vision and Pattern Recognition and 46 papers in Computer Networks and Communications. Recurrent topics in Mattias O’Nils's work include Embedded Systems Design Techniques (34 papers), CCD and CMOS Imaging Sensors (34 papers) and Energy Efficient Wireless Sensor Networks (25 papers). Mattias O’Nils is often cited by papers focused on Embedded Systems Design Techniques (34 papers), CCD and CMOS Imaging Sensors (34 papers) and Energy Efficient Wireless Sensor Networks (25 papers). Mattias O’Nils collaborates with scholars based in Sweden, Italy and Austria. Mattias O’Nils's co-authors include Jan Lundgren, Axel Jantsch, Paolo Sommella, Marco Carratù, Bengt Oelmann, Naeem Ahmad, Benny Thörnberg, Consolatina Liguori, Khurram Shahzad and Faisal Z. Qureshi and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Mattias O’Nils

129 papers receiving 821 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mattias O’Nils Sweden 15 308 301 290 171 102 146 899
Zhi Zhang China 14 228 0.7× 468 1.6× 192 0.7× 99 0.6× 602 5.9× 62 1.4k
M. Gorgoń Poland 15 157 0.5× 338 1.1× 34 0.1× 47 0.3× 132 1.3× 51 583
Liang Cheng United States 21 486 1.6× 182 0.6× 853 2.9× 50 0.3× 101 1.0× 127 1.4k
Gangyong Jia China 17 174 0.6× 113 0.4× 467 1.6× 60 0.4× 104 1.0× 73 837
Shaojing Su China 17 320 1.0× 223 0.7× 241 0.8× 9 0.1× 289 2.8× 86 987
B. Naresh Kumar Reddy India 19 582 1.9× 46 0.2× 335 1.2× 203 1.2× 138 1.4× 94 1.0k
Tinghuan Chen Hong Kong 11 214 0.7× 212 0.7× 42 0.1× 116 0.7× 177 1.7× 48 650
Tiago Gomes Portugal 14 330 1.1× 150 0.5× 367 1.3× 112 0.7× 141 1.4× 60 962
Asma Benmessaoud Gabis Algeria 13 271 0.9× 242 0.8× 187 0.6× 22 0.1× 262 2.6× 22 903
Giuseppe Coviello Italy 16 361 1.2× 64 0.2× 161 0.6× 37 0.2× 42 0.4× 86 763

Countries citing papers authored by Mattias O’Nils

Since Specialization
Citations

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

Fields of papers citing papers by Mattias O’Nils

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mattias O’Nils. 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 Mattias O’Nils. The network helps show where Mattias O’Nils may publish in the future.

Co-authorship network of co-authors of Mattias O’Nils

This figure shows the co-authorship network connecting the top 25 collaborators of Mattias O’Nils. A scholar is included among the top collaborators of Mattias O’Nils 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 Mattias O’Nils. Mattias O’Nils 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.
O’Nils, Mattias, et al.. (2025). Cross-Section-Based Method for LiDAR Dataset Generation With Multipath-Resilient Ground Truth. IEEE Transactions on Instrumentation and Measurement. 74. 1–11.
2.
3.
Carratù, Marco, et al.. (2023). An innovative method for log diameter measurements based on deep learning. abs 1804 2767. 1–6. 1 indexed citations
4.
O’Nils, Mattias, et al.. (2023). Factory-Based Vibration Data for Bearing-Fault Detection. Data. 8(7). 115–115. 9 indexed citations
5.
6.
Sommella, Paolo, et al.. (2022). A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss. Diagnostics. 13(1). 72–72. 46 indexed citations
7.
Sommella, Paolo, et al.. (2022). Recent Advances in Diagnosis of Skin Lesions Using Dermoscopic Images Based on Deep Learning. IEEE Access. 10. 95716–95747. 21 indexed citations
8.
O’Nils, Mattias, et al.. (2022). Improving Deep Learning Based Anomaly Detection on Multivariate Time Series Through Separated Anomaly Scoring. IEEE Access. 10. 108194–108204. 6 indexed citations
9.
Jantsch, Axel, et al.. (2021). Impact of Input Data on Intelligence Partitioning Decisions for IoT Smart Camera Nodes. Electronics. 10(16). 1898–1898. 2 indexed citations
10.
Fedorov, Igor, et al.. (2020). A Two-Layer 3-D Reconstruction Method and Calibration for Multicamera-Based Volumetric Positioning and Characterization. IEEE Transactions on Instrumentation and Measurement. 70. 1–9. 2 indexed citations
11.
Ahmad, Naeem, et al.. (2014). Performance analysis of bi-level image compression methods for machine vision embedded applications. IEEE Sensors Journal.
12.
Ahmad, Naeem, et al.. (2014). Analysis of change coding for data reduction in wireless visual sensor network. IEEE Transactions on Industrial Informatics.
13.
Ahmad, Naeem, et al.. (2014). Complexity Analysis of Vision Functions for Comparison of Wireless Smart Cameras. International Journal of Distributed Sensor Networks. 10(1). 710685–710685. 6 indexed citations
14.
O’Nils, Mattias, et al.. (2010). Exploration of local and central processing for a wireless camera based sensor node. KTH Publication Database DiVA (KTH Royal Institute of Technology). 147–150. 21 indexed citations
15.
O’Nils, Mattias, et al.. (2010). On the number representation in sub-expression sharing. 17–20. 5 indexed citations
16.
O’Nils, Mattias, et al.. (2007). C++ based System Synthesis of Real-Time Video Processing Systems targeting FPGA Implementation. 15. 1–7. 3 indexed citations
17.
O’Nils, Mattias, et al.. (2005). A Generalized Architecture for Hardware Synthesis of Spatio-Temporal Memory Models for Image Processing Systems. International Conference on Systems, Signals and Image Processing. 361–365. 2 indexed citations
18.
O’Nils, Mattias, et al.. (2004). Cubic Vector Median Filter for Noise Reduction and Improvement of Compression Efficiency. International Conference on Systems, Signals and Image Processing. 263–266. 1 indexed citations
19.
Lundgren, Jan, et al.. (2004). Taking mixed-signal substrate noise coupling simulation to the behavioral level using SystemC. 201–205. 3 indexed citations
20.
O’Nils, Mattias, et al.. (2004). A comparison between local and global memory allocation for FPGA implementation of real-time video processing systems. 429–432. 9 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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