Browsing Publikasjoner fra CRIStin by Journals "Lecture Notes in Computer Science"
Now showing items 1-20 of 20
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Ant colony optimisation-based classification using two-dimensional polygons
(Peer reviewed; Journal article, 2016) -
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation
(Journal article; Peer reviewed, 2019) -
Concurrent Computing with Shared Replicated Memory
(Chapter; Peer reviewed, 2019) -
Cyclostationary Random Number Sequences for the Tsetlin Machine
(Peer reviewed; Journal article, 2022)The Tsetlin Machine (TM) constitutes an emerging machine learning algorithm that has shown competitive performance on several benchmarks. The underlying concept of the TM is propositional logic determined by a group of ... -
Digital Volunteers in Disaster Response : Accessibility Challenges
(Chapter; Peer reviewed, 2019) -
Eventual Consistency Formalized
(Chapter; Peer reviewed, 2019) -
Exploring Multilingual Word Embedding Alignments in BERT Models : A Case Study of English and Norwegian
(Lecture Notes in Computer Science; no. 14381, Journal article; Peer reviewed, 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 ... -
Generating Executable Code from High-Level Social or Socio-Ecological Model Descriptions
(Chapter; Peer reviewed, 2019) -
Identifying unreliable sensors without a knowledge of the ground truth in deceptive environments
(Journal article; Peer reviewed, 2017)This paper deals with the extremely fascinating area of “fusing” the outputs of sensors without any knowledge of the ground truth. In an earlier paper, the present authors had recently pioneered a solution, by mapping ... -
The Influence of Human Walking Activities on the Doppler Characteristics of Non-stationary Indoor Channel Models
(Chapter; Peer reviewed, 2019)This paper analyzes the time-variant (TV) Doppler power spectral density of a 3D non-stationary fixed-to-fixed indoor channel simulator after feeding it with realistic trajectories of a walking person. The trajectories of ... -
Modality and uncertainty in data visualizations : A corpus approach to the use of connecting lines
(Journal article; Peer reviewed, 2020) -
On using "Stochastic learning on the line" to design novel distance estimation methods
(Journal article; Peer reviewed, 2018) -
Perceivability of Map Information for Disaster Situations for People with Low Vision
(Chapter; Peer reviewed, 2019) -
Responsible AI and Analytics for an Ethical and Inclusive Digitized Society
(Lecture Notes in Computer Science (LNCS);, Book, 2021) -
RF-Based Human Activity Recognition : A Non-stationary Channel Model Incorporating the Impact of Phase Distortions
(Chapter; Peer reviewed, 2019)This paper proposes a non-stationary channel model that captures the impact of the time-variant (TV) phase distortion caused by hardware imperfections. The model allows for studying the spectrogram of in-home radio channels ... -
Sharing, Cooperation or Collective Action? A Research Agenda for Online Interaction in Digital Global Governance
(International Conference on Electronic Participation;, Peer reviewed; Conference object, 2023)Digital technologies are increasingly used to support governance at the global level. However, the global level has received very little attention in digital governance research. Global governance differs from national ... -
The Dreaming Variational Autoencoder for Reinforcement Learning Environments
(Lecture Notes in Artificial Intelligence, Journal article; Peer reviewed, 2018)Reinforcement learning has shown great potential in generalizing over raw sensory data using only a single neural network for value optimization. There are several challenges in the current state-of-the-art reinforcement ... -
Towards a deep reinforcement learning approach for Tower Line Wars
(Lecture Notes in Artificial Intelligence, Journal article; Peer reviewed, 2017)There have been numerous breakthroughs with reinforcement learning in the recent years, perhaps most notably on Deep Reinforcement Learning successfully playing and winning relatively advanced computer games. There is ... -
Universal design of ICT for emergency management: A systematic literature review and research agenda
(Journal article; Peer reviewed, 2018) -
Unsupervised State Representation Learning in Partially Observable Atari Games
(Lecture Notes in Computer Science; no. 14185, Journal article; Peer reviewed, 2023)State representation learning aims to capture latent factors of an environment. Although some researchers realize the connections between masked image modeling and contrastive representation learning, the effort is focused ...