Browsing by Subject "Deep learning"
Now showing items 1-20 of 22
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Algorithms for Quality Optimization in Omnidirectional Video
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2022)Omnidirectional video (ODV) is a recent imaging technology, which is currently getting increasingly popular thanks to its ability to create an immersive and interactive viewing experience. Nowadays, viewing ODV is becoming ... -
Data-driven enhancement of cubic phase stability in mixed-cation perovskites
(2021)Mixing cations has been a successful strategy in perovskite synthesis by solution-processing, delivering improvements in the thermodynamic stability as well as in the lattice parameter control. Unfortunately, the relation ... -
Data-driven time propagation of quantum systems with neural networks
(2022)We investigate the potential of supervised machine learning to propagate a quantum system in time. While Markovian dynamics can be learned easily, given a sufficient amount of data, non-Markovian systems are nontrivial and ... -
Data-driven time propagation of quantum systems with neural networks
(2022)We investigate the potential of supervised machine learning to propagate a quantum system in time. While Markovian dynamics can be learned easily, given a sufficient amount of data, non-Markovian systems are nontrivial and ... -
Deep Convolutional Neural Networks for estimating lens distortion parameters
(2019)In this paper we present a convolutional neural network (CNN) to predict multiple lens distortion parameters from a single input image. Unlike other methods, our network is suitable to create high resolution output as ... -
Deep Cross-Modal Alignment in Audio-Visual Speech Recognition
(Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2021)Modern studies in cognitive psychology have demonstrated that speech perception is a multimodal process, as opposed to a purely auditory one with visual carryover as in the classic view. This led researchers to investigate ... -
DeepStereoBrush: Interactive Depth Map Creation
(2018)In this paper, we introduce a novel interactive depth map creation approach for image sequences which uses depth-scribbles as input at user-defined keyframes. These scribbled depth values are then propagated within these ... -
Design of AI-based lane changing modules in connected and autonomous vehicles: a survey
(2022)Lane changing is one of the complex driving tasks as it requires the vehicle to be aware of its highlydynamic surrounding environment, make decisions, and enact them in a timely manner. By exploiting both sensors and ... -
Drone image segmentation using machine and deep learning for mapping Irish bog vegetation communities
(2020)The application of drones has recently revolutionised the mapping of wetlands due to their high spatial resolution and the flexibility in capturing images. In this study, the drone imagery was used to map key vegetation ... -
Egocentric Gesture Recognition for Head-Mounted AR devices
(2018)Natural interaction with virtual objects in AR/VR environments makes for a smooth user experience. Gestures are a natural extension from real world to augmented space to achieve these interactions. Finding discriminating ... -
Exploration of Deep Learning Techniques for Natural Image Matting
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)Natural image matting is the process of estimating the opacity mask between the foreground object and the background in any type of image. This technique has manifold applications in image and video processing and ... -
Four-dimensional photonic micro-actuators for microfluidics applications
(2020)Herein we review aspects of leading-edge research and innovation in Materials Sciencethatexploits big data and Machine Learning(ML), two computer science conceptsthat combine to yield computationalintelligence. ML can ... -
A Geometry-Sensitive Approach for Photographic Style Classification
(2018)Photographs are characterized by different compositional attributes like the Rule of Thirds, depth of field, vanishing-lines etc. The presence or absence of one or more of these attributes contributes to the overall ... -
Improved Perceptions of Autonomous Vehicles In Urban Mobility Environment Through Deep learning Object Detection Algorithms
(Trinity College Dublin. School of Engineering. Disc of Civil Structural & Environmental Eng, 2024)Autonomous Vehicles (AVs) or self-driving cars have become the most exciting area of research in the field of transportation in the last decade. Implementation of AVs in real-world requires further investigation especially ... -
Investigating the use of recurrent motion modelling for speech gesture generation
(2018)The growing use of virtual humans demands generating increasingly realistic behavior for them while minimizing cost and time. Gestures are a key ingredient for realistic and engaging virtual agents and consequently automatized ... -
Probabilistic Color Modelling of Clothing Items
(2020)Color modelling and extraction is an important topic in fashion. It can help build a wide range of applications,for example, recommender systems, color-based retrieval, fashion design, etc. We aim to develop and test models ... -
Quantum transport in 2D materials: Theoretical and computational optimisation of large heterostructures with spintronics properties
(Trinity College Dublin. School of Physics. Discipline of Physics, 2023)Graphene is a monolayer of carbon atoms arranged in a hexagonal lattice, making it the thinnest and strongest material known to man. Its exceptional electronic and thermal properties have generated great interest for its ... -
Reflections on the Financial and Ethical Implications of Music Generated by Artificial Intelligence
This work analyses the financial and ethical implications of music generated by Artificial Intelligence (AI). The primary concern of this work relates to issues of employment in the music industry challenged by AI ... -
Semantic image segmentation based on spatial relationships and inexact graph matching
(2020)We propose a method for semantic image segmentation, combining a deep neural network and spatial relationships between image regions, encoded in a graph representation of the scene. Our proposal is based on inexact graph ... -
Towards Generating Ambisonics Using Audio-Visual Cue for Virtual Reality
(2019)Ambisonics i.e., a full-sphere surround sound, is quintessential with 360◦ visual content to provide a realistic virtual reality (VR) experience. While 360◦ visual content capture gained a tremendous boost recently, ...