Morten Goodwin

Orcid: 0000-0001-6331-702X

According to our database1, Morten Goodwin authored at least 157 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Towards misinformation mitigation on social media: novel user activity representation for modeling societal acceptance.
J. Comput. Soc. Sci., April, 2024

Towards safe and sustainable reinforcement learning for real-time strategy games.
Inf. Sci., 2024

Maximum Manifold Capacity Representations in State Representation Learning.
CoRR, 2024

A Manifold Representation of the Key in Vision Transformers.
CoRR, 2024

MapAI: Precision in Building Segmentation.
CoRR, 2024

TRAPL: Transformer-Based Patch Learning for Enhancing Semantic Representations Using Aggregated Features to Estimate Patch-Class Distribution.
Proceedings of the Artificial Intelligence XLI, 2024

Optimizing Autonomous Vehicle Racing Using Reinforcement Learning with Pre-trained Embeddings for Dimensionality Reduction.
Proceedings of the Artificial Intelligence XLI, 2024

NER Explainability Framework: Utilizing LIME to Enhance Clarity and Robustness in Named Entity Recognition.
Proceedings of the Artificial Intelligence XLI, 2024

PlanBERT: From Messy Zonal Plans to Informative Vector Embeddings.
Proceedings of the Artificial Intelligence XLI, 2024

Streamlining Attention for Text Classification: Sequence Length Reduction with Pooling Attention.
Proceedings of the Artificial Intelligence XLI, 2024

A Dataset for Adapting Recommender Systems to the Fashion Rental Economy.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Towards Robust Road Quality Detection Using Different Detection Models.
Proceedings of the Artificial Intelligence Applications and Innovations, 2024

State Representation Learning Using an Unbalanced Atlas.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise.
IEEE Trans. Games, December, 2023

SleepXAI: An explainable deep learning approach for multi-class sleep stage identification.
Appl. Intell., July, 2023

Using Tsetlin Machine to discover interpretable rules in natural language processing applications.
Expert Syst. J. Knowl. Eng., May, 2023

A multi-step finite-state automaton for arbitrarily deterministic Tsetlin Machine learning.
Expert Syst. J. Knowl. Eng., May, 2023

Harnessing Attention Mechanisms: Efficient Sequence Reduction using Attention-based Autoencoders.
CoRR, 2023

DeNISE: Deep Networks for Improved Segmentation Edges.
CoRR, 2023

Loss and Reward Weighing for increased learning in Distributed Reinforcement Learning.
CoRR, 2023

Contrastive Transformer: Contrastive Learning Scheme with Transformer innate Patches.
CoRR, 2023

Unsupervised Representation Learning in Partially Observable Atari Games.
CoRR, 2023

Distinct Sequential Models for Inference Boosting.
Proceedings of the Artificial Intelligence XL, 2023

A Contrastive Learning Scheme with Transformer Innate Patches.
Proceedings of the Artificial Intelligence XL, 2023

ReFrogID: Pattern Recognition for Pool Frog Identification Using Deep Learning and Feature Matching.
Proceedings of the Artificial Intelligence XL, 2023

CorrEmbed: Evaluating Pre-trained Model Image Similarity Efficacy with a Novel Metric.
Proceedings of the Artificial Intelligence XL, 2023

A contrastive learning approach for individual re-identification in a wild fish population.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

A comparison between Tsetlin machines and deep neural networks in the context of recommendation systems.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

DeNISE: Deep Networks for Improved Segmentation Edges.
Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Transfer Learning Through Knowledge-Infused Representations with Contextual Experts.
Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Natural Language Modeling with the Tsetlin Machine.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Applications, 2023

Unsupervised State Representation Learning in Partially Observable Atari Games.
Proceedings of the Computer Analysis of Images and Patterns, 2023

2022
On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

A relational tsetlin machine with applications to natural language understanding.
J. Intell. Inf. Syst., 2022

Development of a Simulator for Prototyping Reinforcement Learning-Based Autonomous Cars.
Informatics, 2022

Deep Reinforcement Learning with Swin Transformer.
CoRR, 2022

Improving the Diversity of Bootstrapped DQN via Noisy Priors.
CoRR, 2022

Temperate fish detection and classification: a deep learning based approach.
Appl. Intell., 2022

Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples.
Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Knowledge Infused Representations Through Combination of Expert Knowledge and Original Input.
Proceedings of the Nordic Artificial Intelligence Research and Development, 2022

Contrasting Axial T2W MRI for Prostate Cancer Triage: A Self-Supervised Learning Approach.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Multi-Planar T2W MRI for an Improved Prostate Cancer Lesion Classification.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Robust Interpretable Text Classification against Spurious Correlations Using AND-rules with Negation.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Sleep Stage Identification based on Single-Channel EEG Signals using 1-D Convolutional Autoencoders.
Proceedings of the IEEE International Conference on E-health Networking, 2022

ITSC Fault Diagnosis in Permanent Magnet Synchronous Motor Drives Using Shallow CNNs.
Proceedings of the Engineering Applications of Neural Networks, 2022

An Exploration of Semi-supervised Text Classification.
Proceedings of the Engineering Applications of Neural Networks, 2022

Towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles.
Proceedings of the Engineering Applications of Neural Networks, 2022

An Accurate Convolutional Neural Networks Approach to Wound Detection for Farmed Salmon.
Proceedings of the Engineering Applications of Neural Networks, 2022

Brain Tumour Segmentation on 3D MRI Using Attention V-Net.
Proceedings of the Engineering Applications of Neural Networks, 2022

CaiRL: A High-Performance Reinforcement Learning Environment Toolkit.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

Socially Fair Mitigation of Misinformation on Social Networks via Constraint Stochastic Optimization.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Deep Learning for Classifying Physical Activities from Accelerometer Data.
Sensors, 2021

Positionless aspect based sentiment analysis using attention mechanism.
Knowl. Based Syst., 2021

Learning Automata-based Misinformation Mitigation via Hawkes Processes.
Inf. Syst. Frontiers, 2021

Increasing sample efficiency in deep reinforcement learning using generative environment modelling.
Expert Syst. J. Knowl. Eng., 2021

Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook.
CoRR, 2021

Self-transfer learning via patches: A prostate cancer triage approach based on bi-parametric MRI.
CoRR, 2021

Expert Q-learning: Deep Q-learning With State Values From Expert Examples.
CoRR, 2021

Distributed Word Representation in Tsetlin Machine.
CoRR, 2021

Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability.
IEEE Access, 2021

ORACLE: End-to-End Model Based Reinforcement Learning.
Proceedings of the Artificial Intelligence XXXVIII, 2021

Modelling Emotion Dynamics in Chatbots with Neural Hawkes Processes.
Proceedings of the Artificial Intelligence XXXVIII, 2021

Improving Prostate Whole Gland Segmentation In T2-Weighted MRI With Synthetically Generated Data.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

An Evaluation of Autonomous Car Simulators and Their Applicability for Supervised and Reinforcement Learning.
Proceedings of the Intelligent Technologies and Applications, 2021

Automatic Sleep Stage Identification with Time Distributed Convolutional Neural Network.
Proceedings of the International Joint Conference on Neural Networks, 2021

Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing.
Proceedings of the Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, 2021

Convolutional Regression Tsetlin Machine: An Interpretable Approach to Convolutional Regression.
Proceedings of the ICMLT 2021: 6th International Conference on Machine Learning Technologies, Jeju Island, Republic of Korea, April 23, 2021

Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling.
Proceedings of the 38th International Conference on Machine Learning, 2021

Interpretability in Word Sense Disambiguation using Tsetlin Machine.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

An Interpretable Word Sense Classifier for Human Explainable Chatbot.
Proceedings of the Agents and Artificial Intelligence - 13th International Conference, 2021

Enhancing Interpretable Clauses Semantically using Pretrained Word Representation.
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021

Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Distributed Learning Automata-based S-learning scheme for classification.
Pattern Anal. Appl., 2020

Towards safe reinforcement-learning in industrial grid-warehousing.
Inf. Sci., 2020

Combining a context aware neural network with a denoising autoencoder for measuring string similarities.
Comput. Speech Lang., 2020

A Regression Tsetlin Machine with Integer Weighted Clauses for Compact Pattern Representation.
CoRR, 2020

A team of pursuit learning automata for solving deterministic optimization problems.
Appl. Intell., 2020

Distributed learning automata-based scheme for classification using novel pursuit scheme.
Appl. Intell., 2020

Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

On Obtaining Classification Confidence, Ranked Predictions and AUC with Tsetlin Machines.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines.
Proceedings of the Artificial Intelligence XXXVII, 2020

CostNet: An End-to-End Framework for Goal-Directed Reinforcement Learning.
Proceedings of the Artificial Intelligence XXXVII, 2020

A Novel Multi-step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning.
Proceedings of the Artificial Intelligence XXXVII, 2020

Deep 3D Convolution Neural Network for Alzheimer's Detection.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Semantic Decay Filter for Event Detection.
Proceedings of the 17th International Conference on Information Systems for Crisis Response and Management, 2020

Environment Sound Classification Using Multiple Feature Channels and Attention Based Deep Convolutional Neural Network.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Interpretable Option Discovery Using Deep Q-Learning and Variational Autoencoders.
Proceedings of the Intelligent Technologies and Applications, 2020

Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing.
Proceedings of the Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 2020

Integer Weighted Regression Tsetlin Machines.
Proceedings of the Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 2020

Road Detection for Reinforcement Learning Based Autonomous Car.
Proceedings of the ICISS 2020: The 3rd International Conference on Information Science and System, 2020

2019
Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation.
EURASIP J. Inf. Secur., 2019

A Neural Turing~Machine for Conditional Transition Graph Modeling.
CoRR, 2019

The Convolutional Tsetlin Machine.
CoRR, 2019

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications.
IEEE Access, 2019

Not a Target. A Deep Learning Approach for a Warning and Decision Support System to Improve Safety and Security of Humanitarian Aid Workers.
Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

A Tsetlin Machine with Multigranular Clauses.
Proceedings of the Artificial Intelligence XXXVI, 2019

Towards Model-Based Reinforcement Learning for Industry-Near Environments.
Proceedings of the Artificial Intelligence XXXVI, 2019

Genetic Algorithm Modeling for Photocatalytic Elimination of Impurity in Wastewater.
Proceedings of the Intelligent Systems and Applications, 2019

Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

The Use of Artificial Intelligence in Disaster Management - A Systematic Literature Review.
Proceedings of the 5th International Conference on Information and Communication Technologies for Disaster Management, 2019

An Iterative Information Retrieval Approach from Social Media in Crisis Situations.
Proceedings of the 5th International Conference on Information and Communication Technologies for Disaster Management, 2019

Causality-based Social Media Analysis for Normal Users Credibility Assessment in a Political Crisis.
Proceedings of the 25th Conference of Open Innovations Association, 2019

The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems.
Proceedings of the Progress in Artificial Intelligence, 2019

Modelling of Compressors in an Industrial CO _2 -Based Operational Cooling System Using ANN for Energy Management Purposes.
Proceedings of the Engineering Applications of Neural Networks, 2019

2018
Combining a Context Aware Neural Network with a Denoising Autoencoder for Measuring String Similarities.
CoRR, 2018

The Dreaming Variational Autoencoder for Reinforcement Learning Environments.
Proceedings of the Artificial Intelligence XXXV, 2018

Effect of Data from Neighbouring Regions to Forecast Dengue Incidences in Different Regions of Philippines Using Artificial Neural Networks.
Proceedings of the 31st Norsk Informatikkonferanse, 2018

A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines.
Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

The Role of Artificial Intelligence in Social Media Big data Analytics for Disaster Management -Initial Results of a Systematic Literature Review.
Proceedings of the 5th International Conference on Information and Communication Technologies for Disaster Management, 2018

Deep CNN-ELM Hybrid Models for Fire Detection in Images.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Deep Neural Networks for Prediction of Exacerbations of Patients with Chronic Obstructive Pulmonary Disease.
Proceedings of the Engineering Applications of Neural Networks, 2018

Neuroevolution of Actively Controlled Virtual Characters - An Experiment for an Eight-Legged Character.
Proceedings of the Engineering Applications of Neural Networks, 2018

A Multi-layer Feed Forward Neural Network Approach for Diagnosing Diabetes.
Proceedings of the 11th International Conference on Developments in eSystems Engineering, 2018

Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

2017
On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments.
IEEE Trans. Cybern., 2017

PolyACO+: a multi-level polygon-based ant colony optimisation classifier.
Swarm Intell., 2017

A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisation.
Proceedings of the Artificial Intelligence XXXIV, 2017

Towards a Deep Reinforcement Learning Approach for Tower Line Wars.
Proceedings of the Artificial Intelligence XXXIV, 2017

FlashRL: A Reinforcement Learning Platform for Flash Games.
Proceedings of the 30th Norsk Informatikkonferanse, 2017

Towards Open Domain Chatbots - A GRU Architecture for Data Driven Conversations.
Proceedings of the Internet Science, 2017

Deep Convolutional Neural Networks for Fire Detection in Images.
Proceedings of the Engineering Applications of Neural Networks, 2017

Vector representation of non-standard spellings using dynamic time warping and a denoising autoencoder.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments.
Proceedings of the Advanced Data Mining and Applications - 13th International Conference, 2017

2016
A pattern recognition approach for peak prediction of electrical consumption.
Integr. Comput. Aided Eng., 2016

Adaptive Task Assignment in Online Learning Environments.
Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics, 2016

Deep Learning for Social Media Analysis in Crises Situations (Position paper).
Proceedings of the 29th Annual Workshop of the Swedish Artificial Intelligence Society, 2016

Towards Evacuation Planning of Groups with Genetic Algorithms.
Proceedings of the 29th Annual Workshop of the Swedish Artificial Intelligence Society, 2016

Information Abstraction from Crises Related Tweets Using Recurrent Neural Network.
Proceedings of the Artificial Intelligence Applications and Innovations, 2016

Teaching Programming to Large Student Groups through Test Driven Development - Comparing Established Methods with Teaching based on Test Driven Development.
Proceedings of the CSEDU 2016, 2016

Distributed learning automata for solving a classification task.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

Optimizing PolyACO Training with GPU-Based Parallelization.
Proceedings of the Swarm Intelligence - 10th International Conference, 2016

Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons.
Proceedings of the Swarm Intelligence - 10th International Conference, 2016

2015
A spatio-temporal probabilistic model of hazard- and crowd dynamics for evacuation planning in disasters.
Appl. Intell., 2015

Escape planning in realistic fire scenarios with Ant Colony Optimisation.
Appl. Intell., 2015

On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth.
Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2015

AIs for Dominion Using Monte-Carlo Tree Search.
Proceedings of the Current Approaches in Applied Artificial Intelligence, 2015

Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem.
Proceedings of the Current Approaches in Applied Artificial Intelligence, 2015

2014
A Novel Strategy for Solving the Stochastic Point Location Problem Using a Hierarchical Searching Scheme.
IEEE Trans. Cybern., 2014

Evaluating prediction models for electricity consumption.
Proceedings of the 27th Norsk Informatikkonferanse, 2014

Predicting Source Code Quality with Static Analysis and Machine Learning.
Proceedings of the 27th Norsk Informatikkonferanse, 2014

On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling.
Proceedings of the 17th IEEE International Conference on Computational Science and Engineering, 2014

2013
Towards automatic assessment of government web sites.
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics, 2013

Ant Colony Optimisation for Planning Safe Escape Routes.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

A Spatio-temporal Probabilistic Model of Hazard and Crowd Dynamics in Disasters for Evacuation Planning.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

2012
A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem.
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012

Following the WCAG 2.0 Techniques: Experiences from Designing a WCAG 2.0 Checking Tool.
Proceedings of the Computers Helping People with Special Needs, 2012

2011
A solution to the exact match on rare item searches: introducing the lost sheep algorithm.
Proceedings of the International Conference on Web Intelligence, Mining and Semantics, 2011

2010
Automatic Checking of Alternative Texts on Web Pages.
Proceedings of the Computers Helping People with Special Needs, 2010

Accessibility of eGovernment Web Sites: Towards a Collaborative Retrofitting Approach.
Proceedings of the Computers Helping People with Special Needs, 2010

2009
Benchmarking e-Government - A Comparative Review of Three International Benchmarking Studies.
Proceedings of the Third International Conference on the Digital Society (ICDS 2009), 2009

Is It Possible to Predict the Manual Web Accessibility Result Using the Automatic Result?
Proceedings of the Universal Access in Human-Computer Interaction. Applications and Services, 2009

2008
Monitoring Accessibility of Governmental Web Sites in Europe.
Proceedings of the Computers Helping People with Special Needs, 2008

2007
Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation.
IEEE Trans. Syst. Man Cybern. Part B, 2007

2006
A Proposed Architecture for Large Scale Web Accessibility Assessment.
Proceedings of the Computers Helping People with Special Needs, 2006


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