All Outputs (1381)

Serendipitous Gains of Explaining a Classifier - Artificial versus Human Performance and Annotator Support in an Urgent Instructor-Intervention Model for MOOCs (2023)
Presentation / Conference Contribution
Alrajhi, L., Pereira, F. D., Cristea, A. I., & Alamri, A. (2023, September). Serendipitous Gains of Explaining a Classifier - Artificial versus Human Performance and Annotator Support in an Urgent Instructor-Intervention Model for MOOCs. Paper presented at HT '23: 34th ACM Conference on Hypertext and Social Media, Rome Italy

Determining when instructor intervention is needed, based on learners’ comments and their urgency in massive open online course (MOOC) environments, is a known challenge. To solve this challenge, prior art used autonomous machine learning (ML) models... Read More about Serendipitous Gains of Explaining a Classifier - Artificial versus Human Performance and Annotator Support in an Urgent Instructor-Intervention Model for MOOCs.

Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario (2023)
Presentation / Conference Contribution
Dwan Pereira, F., Oliveira, E., Rodrigues, L., Cabral, L., Oliveira, D., Carvalho, L., Gasevic, D., Cristea, A., Dermeval, D., & Ferreira Mello, R. (2023, September). Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario. Presented at Eighteenth European Conference on Technology Enhanced Learning: ECTEL 2023, Aveiro, Portugal

Automatic code graders, also called Programming Online Judges (OJ), can support students and instructors in introduction to programming courses (CS1). Using OJs in CS1, instructors select problems to compose assignment lists, whereas students submit... Read More about Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario.

Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language (2023)
Presentation / Conference Contribution
Wang, J., Ivrissimtzis, I., Li, Z., Zhou, Y., & Shi, L. (2023, September). Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language. Presented at ECTEL 2023: Eighteenth European Conference on Technology Enhanced Learning, Aveiro, Portugal

Sign languages enable effective communication between deaf and hearing people. Despite years of extensive pedagogical research, learning sign language online comes with a number of difficulties that might be frustrating for some students. Indeed, mos... Read More about Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language.

Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen (2023)
Presentation / Conference Contribution
Alabdulwahab, B., & Lai-Chong Law, E. (2023, August). Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK

The emergence of Natural User Interface (NUI) approximately two decades ago promised to support intuitive and multimodal interactions by leveraging human sensorimotor skills such as touching, speaking, and gazing. Despite the development and introduc... Read More about Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen.

Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair (2023)
Presentation / Conference Contribution
Lai-Chong Law, E., van As, N., & Følstad, A. (2023, August). Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK

Trust is an attitudinal construct that can be sensitive to prior experience, gender, and age. In our study, we explored how trust in a banking chatbot might be shaped by these user characteristics. Statistical analysis of 251 participants, who intera... Read More about Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair.

Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL (2023)
Presentation / Conference Contribution
Wang, J., Ivrissimtzis, I., Li, Z., Zhou, Y., & Shi, L. (2023, August). Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL. Presented at INTERACT 2023: IFIP Conference on Human-Computer Interaction, York

The use of sign language is a highly effective way of communicating with individuals who experience hearing loss. Despite extensive research, many learners find traditional methods of learning sign language, such as web-based question-answer methods,... Read More about Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL.

ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction (2023)
Presentation / Conference Contribution
Yu, Z., Haung, S., Fang, C., Breckon, T., & Wang, J. (2023, June). ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC

Reconstructing two hands from monocular RGB images is challenging due to frequent occlusion and mutual confusion. Existing methods mainly learn an entangled representation to encode two interacting hands, which are incredibly fragile to impaired inte... Read More about ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction.

Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation (2023)
Presentation / Conference Contribution
Li, L., Shum, H. P., & Breckon, T. P. (2023, June). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. Presented at 2023 IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, BC

Whilst the availability of 3D LiDAR point cloud data has significantly grown in recent years, annotation remains expensive and time-consuming, leading to a demand for semisupervised semantic segmentation methods with application domains such as auton... Read More about Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation.

Sliding into the Future: Investigating Sliding Windows in Temporal Graphs (2023)
Presentation / Conference Contribution
Klobas, N., Mertzios, G. B., & Spirakis, P. G. (2023, August). Sliding into the Future: Investigating Sliding Windows in Temporal Graphs. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius (2023)
Presentation / Conference Contribution
Lucke, F., Paulusma, D., & Ries, B. (2023, August). Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

The (Perfect) Matching Cut problem is to decide if a graph G has a (perfect) matching cut, i.e., a (perfect) matching that is also an edge cut of G. Both Matching Cut and Perfect Matching Cut are known to be NP-complete, leading to many complexity re... Read More about Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius.

Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs (2023)
Presentation / Conference Contribution
Johnson, M., Martin, B., Pandey, S., Paulusma, D., Smith, S., & Van Leeuwen, E. J. (2023, August). Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

For any finite set H = {H1,. .. , Hp} of graphs, a graph is H-subgraph-free if it does not contain any of H1,. .. , Hp as a subgraph. In recent work, meta-classifications have been studied: these show that if graph problems satisfy certain prescribed... Read More about Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs.

Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening (2023)
Presentation / Conference Contribution
Issac-Medina, B., Yucer, S., Bhowmik, N., & Breckon, T. (2023, June). Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC

The rapid progress in automatic prohibited object detection within the context of X-ray security screening, driven forward by advances in deep learning, has resulted in the first internationally-recognized, application-focused object detection perfor... Read More about Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening.

Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery (2023)
Presentation / Conference Contribution
Gaus, Y., Bhowmik, N., Issac-Medina, B., Atapour-Abarghouei, A., Shum, H., & Breckon, T. (2023, June). Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC

Anomaly detection is a classical problem within automated visual surveillance, namely the determination of the normal from the abnormal when operational data availability is highly biased towards one class (normal) due to both insufficient sample siz... Read More about Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery.

Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding (2023)
Presentation / Conference Contribution
Mohamed, H. A., Vascon, S., Hibraj, F., James, S., Pilutti, D., Del Bue, A., & Pelillo, M. (2022, August). Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding. Presented at International Conference on Pattern Recognition (ICPR) 2022 International Workshops and Challenge, Montreal, Canada

On Fine-tuned Deep Features for Unsupervised Domain Adaptation (2023)
Presentation / Conference Contribution
Wang, Q., Meng, F., & Breckon, T. (2023, June). On Fine-tuned Deep Features for Unsupervised Domain Adaptation. Presented at IJCNN 2023: International Joint Conference on Neural Networks, Queensland, Australia

Prior feature transformation based approaches to Unsupervised Domain Adaptation (UDA) employ the deep features extracted by pre-trained deep models without fine-tuning them on the specific source or target domain data for a particular domain adaptati... Read More about On Fine-tuned Deep Features for Unsupervised Domain Adaptation.

Addressing Performance Inconsistency in Domain Generalization for Image Classification (2023)
Presentation / Conference Contribution
Stirling, J., & Moubayed, N. A. (2023, June). Addressing Performance Inconsistency in Domain Generalization for Image Classification. Presented at 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia

Domain Generalization (DG) in computer vision aims to replicate the human ability to generalize well under a shift of data distribution, or domain. In recent years, the field of domain generalization has seen a steady increase in average left-out tes... Read More about Addressing Performance Inconsistency in Domain Generalization for Image Classification.

Work in Progress: Evaluation of Security Standards through a Cyber Range using Hackers’ Tactics, Techniques and Procedures (2023)
Presentation / Conference Contribution
Wake, P., Black, S., & Young, J. (2023, July). Work in Progress: Evaluation of Security Standards through a Cyber Range using Hackers’ Tactics, Techniques and Procedures. Presented at 2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Delft, Netherlands

We present a framework for the creation of a cyber range to test the effectiveness of security standards, policies and frameworks. These assets guide organisations on how to protect themselves from cyber threats. They have been created via a variety... Read More about Work in Progress: Evaluation of Security Standards through a Cyber Range using Hackers’ Tactics, Techniques and Procedures.

Fast Deterministic Gathering with Detection on Arbitrary Graphs: The Power of Many Robots (2023)
Presentation / Conference Contribution
Molla, A. R., Mondal, K., & Moses Jr., W. K. (2023, May). Fast Deterministic Gathering with Detection on Arbitrary Graphs: The Power of Many Robots. Presented at 37th IEEE International Parallel & Distributed Processing Symposium, St. Petersburg, Florida, USA

Over the years, much research involving mobile computational entities has been performed. From modeling actual microscopic (and smaller) robots, to modeling software processes on a network, many important problems have been studied in this context. G... Read More about Fast Deterministic Gathering with Detection on Arbitrary Graphs: The Power of Many Robots.

Architecting Selective Refresh based Multi-Retention Cache for Heterogeneous System (ARMOUR) (2023)
Presentation / Conference Contribution
Agarwal, S., Chakraborty, S., & Själander, M. (2023, July). Architecting Selective Refresh based Multi-Retention Cache for Heterogeneous System (ARMOUR). Presented at 2023 60th ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA

The increasing use of chiplets, and the demand for high-performance yet low-power systems, will result in heterogeneous systems that combine both CPUs and accelerators (e.g., general-purpose GPUs). Chiplet based designs also enable the inclusion of e... Read More about Architecting Selective Refresh based Multi-Retention Cache for Heterogeneous System (ARMOUR).

Optimal (degree+1)-Coloring in Congested Clique (2023)
Presentation / Conference Contribution
Coy, S., Czumaj, A., Davies, P., & Mishra, G. (2023, July). Optimal (degree+1)-Coloring in Congested Clique. Presented at ICALP 2023: 50th EATCS International Colloquium on Automata, Languages and Programming, Paderborn, Germany

We consider the distributed complexity of the (degree+1)-list coloring problem, in which each node u of degree d(u) is assigned a palette of d(u) + 1 colors, and the goal is to find a proper coloring using these color palettes. The (degree+1)-list co... Read More about Optimal (degree+1)-Coloring in Congested Clique.