Blar i Fakultet for teknologi, kunst og design (TKD) på emneord "Deep learning"
Viser treff 1-20 av 29
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Advanced passive operating system fingerprinting using machine learning and deep learning
(International Conference on Computer Communications and Networks (ICCCN); 2020 29th International Conference on Computer Communications and Networks (ICCCN), Journal article; Peer reviewed, 2020-09-30)Securing and managing large, complex enterprise network infrastructure requires capturing and analyzing network traffic traces in real-time. An accurate passive Operating System (OS) fingerprinting plays a critical role ... -
Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders
(Computers in Biology and Medicine;Volume 109, June 2019, Journal article; Peer reviewed, 2019-04-26)To estimate the reliability and cognitive states of operator performance in a human-machine collaborative environment, we propose a novel human mental workload (MW) recognizer based on deep learning principles and utilizing ... -
Automated reporting system using deep convolutional neural network in the medical domain
(MAUU;2021, Master thesis, 2021)Nowadays, in the healthcare sector, a massive volume of medical data sources is available. The data is growing at 153 Exabytes in 2013 and an estimated 2,314 exabytes in 2020 (Turner, Gantz et al. 2014). The medical data ... -
Cross-Subject emotion recognition from EEG using Convolutional Neural Networks
(Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Peer reviewed; Journal article, 2020-09-09)Using electroencephalogram (EEG) signals for emotion detection has aroused widespread research concern. However, across subjects emotional recognition has become an insurmountable gap which researchers cannot step across ... -
Deep learning for automated polyp detection and localization in colonoscopy
(Master thesis, 2022)Gastrointestinal (GI) tract comprises organs from mouth to anus. Multiple diseases can occur in the GI tract. Among the different diseases in the digestive system, the most commonly found cancer in the gastrointestinal ... -
Deep Learning for Classifying Physical Activities from Accelerometer Data
(Sensors;Volume 21 / Issue 16, Peer reviewed; Journal article, 2021-08-18)Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening ... -
Deep learning for crop instance segmentation
(ACIT;2022, Master thesis, 2022)This thesis explores object detection with instance segmentation in relation to agriculture. For the purpose of discovering a detection model that could potentially boost robotic greenhouse harvesters with newer and ... -
Deep learning with cellular automaton-based reservoir computing
(Complex Systems;Volume 26, Issue 4, Journal article; Peer reviewed, 2017)Recurrent neural networks (RNNs) have been a prominent concept wiithin artificial intelligence. They are inspired by biological neural net works (BNNs) and provide an intuitive and abstract representation of how BNNs work. ... -
A deep learning-based tool for automatic brain extraction from functional magnetic resonance images of rodents
(Peer reviewed; Journal article, 2021)Removing skull artifacts from functional magnetic images (fMRI) is a well understood and frequently encountered problem. Because the fMRI field has grown mostly due to human studies, many new tools were developed to handle ... -
Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources
(Sensors;Volume 22 / Issue 7, Peer reviewed; Journal article, 2022-04-06)Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them ... -
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 ... -
DoS and DDoS mitigation using Variational Autoencoders
(Computer Networks;Volume 199, 9 November 2021, 108399, Peer reviewed; Journal article, 2021-09-01)DoS and DDoS attacks have been growing in size and number over the last decade and existing solutions to mitigate these attacks are largely inefficient. Compared to other types of malicious cyber attacks, DoS and DDoS ... -
Edge information based image fusion metrics using fractional order differentiation and sigmoidal functions
(IEEE Access;Volume: 8, Journal article; Peer reviewed, 2020)In recent years, the number of image fusion schemes presented by the research community has increased significantly. Measuring the performance of these schemes is an important issue. In this work, we introduce three ... -
EMG Signals based Human Action Recognition via Deep Belief Networks
(IFAC-PapersOnLine;Volume 52, Issue 19, 2019, Journal article; Peer reviewed, 2019-12-24)Electromyography (EMG) signals can be used for action classification. Nonetheless, due to their nonlinear and time-varying properties, it is difficult to classify the EMG signals and it is critical to use appropriate ... -
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
(Information Fusion;Volume 59, July 2020, Peer reviewed; Journal article, 2020-01-31)In recent years, the rapid advances in machine learning (ML) and information fusion has made it possible to endow machines/computers with the ability of emotion understanding, recognition, and analysis. Emotion recognition ... -
Facial emotion recognition using deep learning
(ACIT;2022, Master thesis, 2022)Rapid advancements in Machine Learning (ML) have made it possible to equip computers with the ability to analyze, recognize and understand emotions. Facial Emotion Recognition (FER) is a technology that analyzes facial ... -
Interpretable intrusion detection for next generation of Internet of Things
(Peer reviewed; Journal article, 2023)This paper presents a new framework for intrusion detection in the next-generation Internet of Things. MinMax normalization strategy is used to collect and preprocess data. The Marine Predator algorithm is then used to ... -
Kvasir-Instruments and Polyp Segmentation Using UNet
(Nordic Machine Intelligence (NMI);Vol. 1 No. 1 (2021): MedAI: Transparency in Medical Image Segmentation, Peer reviewed; Journal article, 2021-11-01)This paper aims to describe the methodology used to develop, fine-tune and analyze a UNet model for creating masks for two datasets: Polyp Segmentation and Instrument Segmentation, which are part of MedAI challenge. For ... -
LiDAR-Based Obstacle Detection and Distance Estimation in Navigation Assistance for Visually Impaired
(Lecture Notes in Computer Science;Volume 13309, Conference object, 2022-06-16)People with visual impairments can face challenges with independent navigation and therefore may use traditional aids such as guide dogs, white canes, or a travel companion for navigation assistance. In recent years, ... -
LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification
(Lecture Notes in Computer Science;Volume 12606, Conference object, 2021-02-21)Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks. A key drawback of DNNs is that the training phase can be very computationally expensive. ...