Morten Goodwin

2.4k total citations
94 papers, 1.0k citations indexed

About

Morten Goodwin is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Morten Goodwin has authored 94 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 21 papers in Computer Networks and Communications and 15 papers in Computer Vision and Pattern Recognition. Recurrent topics in Morten Goodwin's work include Optimization and Search Problems (17 papers), Machine Learning and Algorithms (15 papers) and Reinforcement Learning in Robotics (12 papers). Morten Goodwin is often cited by papers focused on Optimization and Search Problems (17 papers), Machine Learning and Algorithms (15 papers) and Reinforcement Learning in Robotics (12 papers). Morten Goodwin collaborates with scholars based in Norway, United Kingdom and Canada. Morten Goodwin's co-authors include Ole‐Christoffer Granmo, Mohan Lal Kolhe, Lei Jiao, Anis Yazidi, Jivitesh Sharma, Christian W. Omlin, Jaziar Radianti, Christian S. Jensen, B. John Oommen and Aditya Gupta and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Cleaner Production.

In The Last Decade

Morten Goodwin

90 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Morten Goodwin Norway	18	426	195	162	93	73	94	1.0k
Chunhong Zhang China	14	487 1.1×	240 1.2×	171 1.1×	149 1.6×	65 0.9×	112	1.0k
Moamin A. Mahmoud Malaysia	20	260 0.6×	174 0.9×	206 1.3×	138 1.5×	45 0.6×	95	1.2k
Ruiyun Yu China	17	292 0.7×	212 1.1×	208 1.3×	122 1.3×	62 0.8×	68	1.0k
Jacek Mańdziuk Poland	18	549 1.3×	101 0.5×	81 0.5×	178 1.9×	55 0.8×	103	1.1k
Hany F. ElYamany Egypt	7	422 1.0×	291 1.5×	155 1.0×	86 0.9×	91 1.2×	15	1.1k
Neil Y. Yen Japan	13	400 0.9×	218 1.1×	234 1.4×	143 1.5×	56 0.8×	53	1.2k
Andreas Konstantinidis Cyprus	16	291 0.7×	385 2.0×	418 2.6×	100 1.1×	62 0.8×	71	1.2k
Antonio M. Mora Spain	19	487 1.1×	66 0.3×	162 1.0×	97 1.0×	89 1.2×	113	1.1k
Jingjing Li China	13	507 1.2×	141 0.7×	186 1.1×	139 1.5×	26 0.4×	54	1.1k
C. B. Sivaparthipan China	14	224 0.5×	109 0.6×	187 1.2×	116 1.2×	44 0.6×	39	1.0k

Countries citing papers authored by Morten Goodwin

Since Specialization

Citations

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

Fields of papers citing papers by Morten Goodwin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Morten Goodwin

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

All Works

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20 of 20 papers shown

Goodwin, Morten, et al.. (2025). A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking. ArXiv.org. 170–179. 3 indexed citations

Goodwin, Morten, et al.. (2024). Deep Reinforcement Learning with Swin Transformers. 205–211. 1 indexed citations

Gupta, Aditya, et al.. (2024). An Interpretable Modular Deep Learning Framework for Video-Based Fall Detection. Applied Sciences. 14(11). 4722–4722. 5 indexed citations

Sørdalen, Tonje Knutsen, et al.. (2023). A contrastive learning approach for individual re-identification in a wild fish population. 4. 3 indexed citations

Goodwin, Morten, et al.. (2023). A comparison between Tsetlin machines and deep neural networks in the context of recommendation systems. arXiv (Cornell University). 4. 3 indexed citations

Granmo, Ole‐Christoffer, et al.. (2023). Exploring the Potential of Model-Free Reinforcement Learning using Tsetlin Machines. 1–8.

Gupta, Aditya, et al.. (2022). Hierarchical Object Detection applied to Fish Species. Duo Research Archive (University of Oslo). 2(1). 3 indexed citations

Goodwin, Morten, et al.. (2022). Development of a Simulator for Prototyping Reinforcement Learning-Based Autonomous Cars. Informatics. 9(2). 33–33. 2 indexed citations

Zhang, Xuan, Lei Jiao, Ole‐Christoffer Granmo, & Morten Goodwin. (2021). On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(10). 6345–6359. 24 indexed citations

10.

Goodwin, Morten, et al.. (2021). Farm-Scale Crop Yield Prediction from Multi-Temporal Data Using Deep Hybrid Neural Networks. Agronomy. 11(12). 2576–2576. 29 indexed citations

11.

Jiao, Lei, et al.. (2021). Positionless aspect based sentiment analysis using attention mechanism. Knowledge-Based Systems. 226. 107136–107136. 37 indexed citations

12.

Goodwin, Morten, et al.. (2021). Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling. Duo Research Archive (University of Oslo). 10–20. 2 indexed citations

13.

Granmo, Ole‐Christoffer, et al.. (2021). Learning Automata-based Misinformation Mitigation via Hawkes Processes. Information Systems Frontiers. 23(5). 1169–1188. 11 indexed citations

14.

Yazidi, Anis, et al.. (2020). Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow. Cognitive Neurodynamics. 14(5). 675–687. 9 indexed citations

15.

Goodwin, Morten, et al.. (2020). Increasing sample efficiency in deep reinforcement learning using generative environment modelling. Expert Systems. 38(7). 6 indexed citations

16.

Goodwin, Morten, et al.. (2020). Towards safe reinforcement-learning in industrial grid-warehousing. Information Sciences. 537. 467–484. 20 indexed citations

17.

Goodwin, Morten, et al.. (2020). A Deep Reinforcement Learning scheme for Battery Energy Management. 1–6. 2 indexed citations

18.

Granmo, Ole‐Christoffer, et al.. (2020). On Obtaining Classification Confidence, Ranked Predictions and AUC with Tsetlin Machines. 662–669. 4 indexed citations

19.

Sharma, Jivitesh, Ole‐Christoffer Granmo, & Morten Goodwin. (2019). Environment Sound Classification using Multiple Feature Channels and Deep Convolutional Neural Networks. arXiv (Cornell University). 8 indexed citations

20.

Goodwin, Morten, et al.. (2018). A Multi-layer Feed Forward Neural Network Approach for Diagnosing Diabetes. 300–305. 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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