Mateus Mendes

1.3k total citations
60 papers, 848 citations indexed

About

Mateus Mendes is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Mateus Mendes has authored 60 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 13 papers in Control and Systems Engineering and 12 papers in Industrial and Manufacturing Engineering. Recurrent topics in Mateus Mendes's work include Fault Detection and Control Systems (9 papers), Industrial Vision Systems and Defect Detection (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Mateus Mendes is often cited by papers focused on Fault Detection and Control Systems (9 papers), Industrial Vision Systems and Defect Detection (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Mateus Mendes collaborates with scholars based in Portugal, Brazil and France. Mateus Mendes's co-authors include José Torres Farinha, Raquel P. F. Guiné, António J. Marques Cardoso, José E.R. Cury, Fernando Gonçalves, Maria João Barroca, Fernando Gomide, Manuel Crisóstomo, A. Paulo Coimbra and Paula Correia and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Food Chemistry.

In The Last Decade

Mateus Mendes

55 papers receiving 799 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mateus Mendes Portugal 15 169 141 133 128 111 60 848
Haochen Liu China 22 74 0.4× 45 0.3× 333 2.5× 131 1.0× 246 2.2× 123 1.5k
Gabriel Avelino Sampedro Philippines 20 108 0.6× 49 0.3× 140 1.1× 87 0.7× 167 1.5× 125 1.1k
Fang Cao China 13 406 2.4× 195 1.4× 80 0.6× 15 0.1× 67 0.6× 56 1.0k
Meenakshi Garg India 13 45 0.3× 50 0.4× 117 0.9× 149 1.2× 330 3.0× 46 986
Zsolt Kemény Hungary 15 311 1.8× 146 1.0× 91 0.7× 55 0.4× 44 0.4× 48 858
Xiaomin Li China 14 291 1.7× 110 0.8× 55 0.4× 120 0.9× 124 1.1× 105 1.5k
Xiaoyan Peng China 23 36 0.2× 607 4.3× 76 0.6× 222 1.7× 136 1.2× 64 1.4k
Junita Mohamad–Saleh Malaysia 19 59 0.3× 111 0.8× 38 0.3× 190 1.5× 390 3.5× 82 1.4k
Hao Chen China 23 29 0.2× 170 1.2× 24 0.2× 223 1.7× 367 3.3× 111 1.5k
Pauline Ong Malaysia 21 140 0.8× 243 1.7× 41 0.3× 333 2.6× 529 4.8× 93 1.7k

Countries citing papers authored by Mateus Mendes

Since Specialization
Citations

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

Fields of papers citing papers by Mateus Mendes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mateus Mendes

This figure shows the co-authorship network connecting the top 25 collaborators of Mateus Mendes. A scholar is included among the top collaborators of Mateus Mendes 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 Mateus Mendes. Mateus Mendes 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.
Mendes, Mateus, et al.. (2024). Comparative analysis of four classification algorithms for fault detection of heat pumps. Energy and Buildings. 316. 114342–114342. 8 indexed citations
2.
Mendes, Mateus, et al.. (2024). Mobile Augmented Reality Application to Evaluate the River Flooding Impact in Coimbra. Applied Sciences. 14(21). 10017–10017. 1 indexed citations
3.
Farinha, José Torres, et al.. (2024). Fault Detection in Industrial Equipment through Analysis of Time Series Stationarity. Algorithms. 17(10). 455–455. 1 indexed citations
4.
Farinha, José Torres, et al.. (2024). Optimising Forest Management Using Multi-Objective Genetic Algorithms. Sustainability. 16(23). 10655–10655. 2 indexed citations
5.
6.
Farinha, José Torres, et al.. (2024). Fault Detection and Prediction for Power Transformers Using Fuzzy Logic and Neural Networks. Energies. 17(2). 296–296. 7 indexed citations
7.
Peixinho, N., Teresa Barata, Carlos Pereira, et al.. (2023). Sunspot Detection Using YOLOv5 in Spectroheliograph H-Alpha Images. Applied Sciences. 13(10). 5833–5833. 5 indexed citations
8.
Mendes, Mateus, et al.. (2023). Hybrid CNN-LSTM Network for Cyberbullying Detection on Social Networks using Textual Contents. International Journal of Advanced Computer Science and Applications. 14(9). 5 indexed citations
9.
Fonseca, Inácio, et al.. (2023). Predicting the Health Status of a Pulp Press Based on Deep Neural Networks and Hidden Markov Models. Energies. 16(6). 2651–2651. 6 indexed citations
10.
Farinha, José Torres, et al.. (2023). Augmented Reality in Maintenance—History and Perspectives. Journal of Imaging. 9(7). 142–142. 9 indexed citations
11.
Mendes, Mateus, et al.. (2022). Improved GRU prediction of paper pulp press variables using different pre-processing methods. Production & Manufacturing Research. 11(1). 11 indexed citations
12.
Mendes, Mateus, et al.. (2022). Forecasting Steel Production in the World—Assessments Based on Shallow and Deep Neural Networks. Applied Sciences. 13(1). 178–178. 5 indexed citations
13.
Mendes, Mateus, et al.. (2021). Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press. Energies. 14(21). 6958–6958. 93 indexed citations
14.
Cruz, Samuel, et al.. (2021). Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network. Journal of Imaging. 7(2). 24–24. 13 indexed citations
15.
Guiné, Raquel P. F., Mateus Mendes, & Fernando Gonçalves. (2019). Optimization of bioactive compound’s extraction conditions from beetroot by means of artificial neural networks (ANN). Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 3 indexed citations
16.
Guiné, Raquel P. F., et al.. (2018). Modeling Through Artificial Neural Networks of the Phenolic Compounds and Antioxidant Activity of Blueberries. Iranian Journal of Chemistry & Chemical Engineering-international English Edition. 37(2). 193–212. 10 indexed citations
17.
Barata, João, et al.. (2017). A Systematic Approach to Design Product Traceability in Industry 4.0: Insights from the Ceramic Industry. Journal of the Association for Information Systems. 1 indexed citations
18.
Guiné, Raquel P. F., et al.. (2014). Convective Drying of Apples: Kinetic Study, Evaluation of Mass Transfer Properties and Data Analysis using Artificial Neural Networks. International Journal of Food Engineering. 10(2). 281–299. 25 indexed citations
19.
Guiné, Raquel P. F., et al.. (2014). Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments. Food Chemistry. 168. 454–459. 106 indexed citations
20.
Castelo‐Branco, Miguel, et al.. (2008). Hierarchical and Parallel Visual Processing in Parkinson Disease: Magnocellular Impairment and Motion Integration Deficits Are Independent. Investigative Ophthalmology & Visual Science. 49(13). 5848–5848. 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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