Browsing TKD - Institutt for informasjonsteknologi by Document Types "Conference object"
Now showing items 41-60 of 171
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Digital Volunteers in Disaster Response: Accessibility Challenges
(Lecture Notes in Artificial Intelligence;Volume 11573, Conference object, 2019-07-04)The emergence of the Digital Humanitarian Volunteer (DHV) movements when disaster strikes have drawn the attention of researchers and practitioners in the emergency management and humanitarian domain. While there are ... -
Disaster Risk Reduction for All? Understanding Intersectionality in Disaster Situations
(IFIP Advances in Information and Communication Technology;Volume 622, Conference object, 2021-07-31)When designing digital services for citizens in a disaster situation, the diversity of its audience and their particular needs are not always sufficiently taken into account. Variables like digital equipment available, ... -
Distance Estimation Methods for Smartphone-Based Navigation Support Systems
(Lecture Notes in Networks and Systems;295, Conference object, 2021-08-03)Distance estimation is a key element of a navigation system. Various methods and instruments are used in distance estimation procedures. The methods and instruments used usually depend on the contexts of the application ... -
DivergentNets: Medical Image Segmentation by Network Ensemble
(CEUR Workshop Proceedings;Vol-2886 - Proceedings of the 3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2021), Conference object, 2021)Detection of colon polyps has become a trending topic in the intersecting fields of machine learning and gastrointestinal endoscopy. The focus has mainly been on per-frame classification. More recently, polyp segmentation ... -
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation
(IEEE International Symposium on Computer-Based Medical Systems; 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2020-09-01)Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image ... -
The Dynamical Landscape of Reservoir Computing with Elementary Cellular Automata
(Conference object, 2021)Reservoir Computing with Cellular Automata (ReCA) is a promising concept by virtue of its potential for efficient hardware implementation and theoretical understanding of Cellular Auotmata (CA). However, ReCA has so far ... -
Effectiveness of Color-Picking Interfaces Among Non-designers
(Lecture Notes in Artificial Intelligence;vol 11792, Conference object, 2019)There are relatively few studies on the effectiveness of color picking interface. This study therefore set out to measure both the efficiency in terms of task completion time and preference of four color-picking interfaces ... -
An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals
(Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Conference object, 2020-09-09)Evaluating operator cognitive workload (CW) levels in human-machine systems based on neurophysiological signals is becoming the basis to prevent serious accidents due to abnormal state of human operators. This study proposes ... -
Emerging Biometric Modalities and their Use: Loopholes in the Terminology of the GDPR and Resulting Privacy Risks
(Conference object, 2021)Technological advancements allow biometric applications to be more omnipresent than in any other time before. This paper argues that in the current EU data protection regulation, classification applications using biometric ... -
Enhanced Learning of Jazz Chords with a Projector Based Piano Keyboard Augmentation
(Lecture Notes in Artificial Intelligence;vol 11937, Conference object, 2019)Learning jazz piano is considered technically difficult. Most people cannot afford private piano tuition and there are many freely available video tutorials on the Internet. This study identified a set of challenging topics ... -
Enhancing Security of Cellular IoT with Identity Federation
(Advances in Intelligent Systems and Computing;Volume 1035, Conference object, 2019-08-15)This paper presents a Cellular Identity Federation solution which both strengthens and simplifies the authentication of Internet of Things (IoT) devices and applications by providing single sign-on between the network ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
(Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
Evolutionary-based automated testing for GraphQL APIs
(GECCO: Genetic and Evolutionary Computation Conference;GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Conference object, 2022)The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces ... -
Evolved Art with Transparent, Overlapping, and Geometric Shapes
(Communications in Computer and Information Science;Volume 1056, Conference object, 2019-11-22)In this work, an evolutionary art project is presented where images are approximated by transparent, overlapping and geometric shapes of different types, e.g., polygons, circles, lines. Genotypes representing features and ... -
Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity
(IEEE Symposium Series on Computational Intelligence (SSCI);2021 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2021-01-24)Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to ... -
Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch
(Chapter; Peer reviewed; Conference object, 2022)With the development of Industry 4.0 technology, modern industries such as Bosch’s welding monitoring witnessed the rapid widespread of machine learning (ML) based data analytical applications, which in the case of welding ... -
ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics
(CIKM: Conference on Information and Knowledge Management;, Chapter; Peer reviewed; Conference object, 2022)Data analytics including machine learning (ML) is essential to extract insights from production data in modern industries. However, industrial ML is affected by: the low transparency of ML towards non-ML experts; poor and ... -
Experiences using three app prototyping tools with different levels of fidelity from a product design student’s perspective
(Lecture Notes in Computer Science;12555, Conference object, 2020-11-18)Prototyping has become a widely embraced technique in different design fields to facilitate early user involvement to ensure that the end-product meets the users’ needs. Each design field has its tools and traditions for ... -
Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian
(Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ... -
Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian
(Chapter; Peer reviewed; Conference object; Journal article, 2023)Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ...