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Deep Composite Face Image Attacks: Generation, Vulnerability and Detection
(Peer reviewed; Journal article, 2023)Face manipulation attacks have drawn the attention of biometric researchers because of their vulnerability to Face Recognition Systems (FRS). This paper proposes a novel scheme to generate Composite Face Image Attacks ... -
Deep Contextual Grid Triplet Network for Context-Aware Recommendation
(Peer reviewed; Journal article, 2023)Modeling contextual information is a vital part of developing effective recommender systems. Still, existing work on recommendation algorithms has generally put limited focus on the effective treatment of contextual ... -
Deep convolutional neural network recovers pure absorbance spectra from highly scatter‐distorted spectra of cells
(Peer reviewed; Journal article, 2020)Infrared spectroscopy of cells and tissues is prone to Mie scattering distortions, which grossly obscure the relevant chemical signals. The state‐of‐the‐art Mie extinction extended multiplicative signal correction (ME‐EMSC) ... -
Deep Crustal Flow Within Postorogenic Metamorphic Core Complexes: Insights From the Southern Western Gneiss Region of Norway
(Journal article; Peer reviewed, 2019)Viscous crustal flow can exhume once deeply buried rocks in postorogenic metamorphic core complexes (MCCs). While migmatite domes record the flow dynamics of anatectic crust, the mechanics and kinematics of solid‐state ... -
A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering
(Journal article; Peer reviewed, 2023)An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data ... -
Deep digital maintenance
(Journal article; Peer reviewed, 2017)With the emergence of Industry 4.0, maintenance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset ... -
A Deep Dive into Green Infrastructure Failures using Fault Tree Analysis
(Journal article; Peer reviewed, 2024)Green Infrastructure has transformed traditional urban stormwater management systems by fostering a wide range of service functions. Despite their popularity, green infrastructure's performance can deteriorate over their ... -
Deep Ensemble Learning for the Automatic Detection of Pneumoconiosis in Coal Worker’s Chest X-ray Radiography
(Peer reviewed; Journal article, 2022)Globally, coal remains one of the natural resources that provide power to the world. Thousands of people are involved in coal collection, processing, and transportation. Particulate coal dust is produced during these ... -
Deep Face Age Progression: A Survey
(Peer reviewed; Journal article, 2021) -
Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace
(Peer reviewed; Journal article, 2021)Due to the severe threat to cyberspace security, detection of online spammers has been a universal concern of academia. Nowadays, prevailing literature of this field almost leveraged various relations to enhance feature ... -
Deep hydration of an Li7-3xLa3Zr2MIIIxO12solid-state electrolyte material: A case study on Al- and Ga-stabilized LLZO
(Peer reviewed; Journal article, 2022)Single crystals of an Li-stuffed, Al- and Ga-stabilized garnet-type solid-state electrolyte material, Li7La3Zr2O12 (LLZO), have been analysed using single-crystal X-ray diffraction to determine the pristine structural state ... -
Deep Hyperspectral Prior: Single-Image Denoising, Inpainting, Super-Resolution
(Chapter, 2019)Deep learning algorithms have demonstrated state-of-the-art performance in various tasks of image restoration. This was made possible through the ability of CNNs to learn from large exemplar sets. However, the latter becomes ... -
A deep learning approach for brain tumor classification using MRI images
(Journal article; Peer reviewed, 2022) -
A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data
(Peer reviewed; Journal article, 2020)Vessels today are being fully monitored, thanks to the advance of sensor technology. The availability of data brings ship intelligence into great attention. As part of ship intelligence, the desire of using advanced ... -
Deep Learning Approaches for Whiteboard Image Quality Enhancement
(Peer reviewed; Journal article, 2019)Different whiteboard image degradations highly reduce the legibility of pen-stroke content as well as the overall quality of the images. Consequently, different researchers addressed the problem through different image ... -
Deep learning as optimal control problems: models and numerical methods
(Journal article; Peer reviewed, 2019)We consider recent work of [11] and [6], where deep learning neuralnetworks have been interpreted as discretisations of an optimal control problemsubject to an ordinary differential equation constraint. We review the first ... -
Deep learning assisted physics-based modeling of aluminum extraction process
(Peer reviewed; Journal article, 2023)Modeling complex physical processes such as the extraction of aluminum is mainly done using pure physics-based models derived from first principles. However, the accuracy of these models can often suffer due to a partial ... -
Deep learning based decomposition for visual navigation in industrial platforms
(Peer reviewed; Journal article, 2021)In the heavy asset industry, such as oil & gas, offshore personnel need to locate various equipment on the installation on a daily basis for inspection and maintenance purposes. However, locating equipment in such GPS ... -
Deep learning based keypoint rejection system for underwater visual ego-motion estimation
(Peer reviewed; Journal article, 2020)Most visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) systems rely heavily on robust keypoint detection and matching. With regards to images taken in the underwater environment, phenomena like ... -
Deep learning based Sequential model for malware analysis using Windows exe API Calls
(Peer reviewed; Journal article, 2020)Malware development has seen diversity in terms of architecture and features. This advancement in the competencies of malware poses a severe threat and opens new research dimensions in malware detection. This study is ...