115 zoekresultaten voor “neural” in de Publieke website
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Functional fluorescent materials and migration dynamics of neural progenitor cells
In this thesis, time-lapse fluorescent microscopy plays a pivotal role in investigating functional materials within living cells as well as the migratory behaviour of neural progenitor cells.
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Automated Machine Learning for Neural Network Verification
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towards stability of delay differential equations with applications to neural networks
Promotor: S.M. Verduyn Lunel, Co-Promotor: O.W. van Gaans
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Efficient Brain Computer Interface Character Speller: Convolutional Neural Network based Methods
A P300-based Brain Computer Interface character speller, also known as P300 speller, has been an important communication pathway, under extensive research, for people who lose motor ability, such as patients with Amyotrophic Lateral Sclerosis or spinal-cord injury because a P300 speller allows human-beings…
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Emergence of Linguistic Universals in Neural Agents via Artificial Language Learning and Communication
Human language is constantly evolving with its linguistic structure being shaped by language users at both individual and population levels. Focusing on the interplay between processes of language acquisition and communicative need in shaping human languages, this thesis introduces a novel computational…
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A brain-wide map of neural activity during complex behaviour
Een belangrijke uitdaging in de neurowetenschappen is het begrijpen hoe neuronen in honderden onderling verbonden hersengebieden sensorische input integreren met eerdere verwachtingen om bewegingen te initiëren en beslissingen te nemen.
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Worlds shaped by words: a cross-linguistic investigation into the neural mechanisms of lexico-syntactic feature production
Op 17 december promoveert Jin Wang. Het Leiden University Centre for Linguistics feliciteert Jin!
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Risk bounds for deep learning
In this thesis, deep learning is studied from a statistical perspective. Convergence rates for the worst case risk bounds of neural network estimators are obtained in the classification, density estimation and linear regression model.
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Developmental effects of polystyrene nanoparticles in the chicken embryo
There is concern about the threat that nanoplastics (NPs) may pose to both wildlife and humans. This thesis explores the mechanisms of toxicity of polystyrene nanoparticles (PS-NPs) in chicken embryo.
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System-level design for efficient execution of CNNs at the edge
A convolutional neural network (CNN) is a biologically inspired algorithm, highly capable at processing images and videos.
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Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
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Deep learning for tomographic reconstruction with limited data
Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.
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Multi-dimensional feature and data mining
In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.
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Solving the Gravitational N-body Problem with Machine Learning
In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.
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Machine learning and computer vision for urban drainage inspections
Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.
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Annelot Bosmana.w.bosman@liacs.leidenuniv.nl | 071 5274799
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Ruis in het brein? De invloed van veroudering op de neurale mechanismen van keuzegedrag
De activiteit van het brein verandert naarmate mensen ouder worden, wat kan leiden tot cognitieve achteruitgang. Door hersendata van muizen en mensen te meten en vergelijken, wil de onderzoeker begrijpen hoe tijdens het ouder worden de ruizigheid van ons brein verandert en keuzegedrag beïnvloedt.
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Long term dynamics of stochastic evolution equations
Promotor: S.M. Verduyn Lunel, Co-promotor: O. van Gaans
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From pixels to patterns: AI-driven image analysis in multiple domains
This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.
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Large scale visual search
Promotor: J.N. Kok, Co-promotor: M.S. Lew
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Understanding deep meta-learning
The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.
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Accurate modeling of the dynamics of dissociative chemisorption on metal surfaces
Fundamental understanding of molecular reactions on metal surfaces is important for improving heterogeneous catalysis.
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Fenying ZangFaculteit der Sociale Wetenschappen
f.zang@fsw.leidenuniv.nl | 071 5272727
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Emily Yuz.yu@liacs.leidenuniv.nl | 071 5272727
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On the optimization of imaging pipelines
In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…
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Automated Machine Learning for Neural Network Verification
Promotie
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Archief
Op deze pagina verzamelen we de presentaties en video's van de Florence Nightingale Colloquia, seminars bij de faculteiten en andere evenementen gehost door het Data Science Onderzoeksprogramma.
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Using Deep Learning Models in Image Processing
Beeldbewerking heeft met de komst van Deep Learning een revolutie doorgemaakt. Dit heeft, in het bijzonder, opmerkelijke voortgang gegeven in het onderzoeksveld variërend van autonome besturing van voertuigen tot medische diagnostiek.
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Numerical exploration of statistical physics
In this thesis, we examine various systems through the lens of several numerical methods.
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Computational optimisation of optical projection tomography for 3D image analysis
Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.
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Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
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Wetenschappelijke publicaties
Een lijst met wetenschappelijke publicaties samengesteld door het team van het TRIXY Expertisecentrum.
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Cognitieve Psychologie
Cognitieve psychologie is de studie van mentale functies, waaronder aandacht, geheugen, bewustzijn, emotie, taal en actiecontrole. Het doel is om de complexe relaties tussen brein, cognitie en gedrag te begrijpen.
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Leukemia treatment & cognitive development
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Machine learning for radio galaxy morphology analysis
We explored how to morphologically classify well-resolved jetted radio-loud active galactic nuclei (RLAGN) in the LOw Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) using machine learning.
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Automated machine learning for dynamic energy management using time-series data
Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…
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Clavis Aurea? Structure-enabled approaches of identifying and optimizing GPCR ligands
Promotores: A.P. IJzerman, H.W.T. van Vlijmen
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Emergence of Linguistic Universals in Neural Agents via Artificial Language Learning and Communication
Promotie
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Publicaties
Disclaimer: Manuscripten die te maken hebben met het Resilience Center zijn alleen voor academische doeleinden en zijn niet bedoeld voor massaverspreiding of kopiëren. Raadpleeg de toepasselijke wetten voor eerlijk gebruik, inclusief de beperkingen van de houders van auteursrechten op publicaties.
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Events
Het LIACS organiseert verschillende lezingenseries, zoals het LCN2 Seminars en de SAILS Lunch Time-seminars.
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Archeologie
De Faculteit Archeologie
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Welkom bij de Leidse Faculteit der Sociale Wetenschappen
Actuele vraagstukken uit zowel Nederland als de internationale gemeenschap, zetten we in om de nieuwsgierigheid van studenten en onderzoekers te prikkelen.
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Worlds shaped by words: A cross-linguistic investigation into the neural mechanisms of lexico-syntactic feature production
Promotie
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Promoveren
Het Leiden University Centre for Linguistics (LUCL) heeft een lange traditie in onderzoek naar de talen van de wereld en beschikt over unieke taalkundige expertise. Bij het LUCL helpen we bij het ontwikkelen van interdisciplinaire benaderingen door de interactie tussen datagestuurd en theorie gestuurd…
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Eetgedrag in de moderne samenleving
Een onderzoek naar hoe mensen eten en drinken tijdens hun dagelijkse routines, en onder welke omstandigheden dit plaatsvindt.
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Technology & Innovation
De onderzoeksgroep Business, Technology & Public Policy van de afdeling Bedrijfswetenschappen van Universiteit leiden houdt zich bezig met het onderzoeken van de dynamische wisselwerking tussen ‘nieuwe’ technologieën en de verschillende belanghebbenden die hiermee interacteren, waaronder consumenten,…
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Misvorming van hart, ogen en zenuwstelsel: nano-plastics verstoren groei
Nano-plastics verstoren de ontwikkeling. Meiru Wang, onderzoeker bij het Instituut Biologie Leiden, keek naar de extreme effecten die piepschuim nano-deeltjes kunnen hebben, met kippenembryo’s als model. Haar resultaten zijn alarmerend. Zeker omdat nano-plastics overal zijn. In de lucht, drijvend door…
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Transfer Learning in Deep Reinforcement Learning and Procedural Content Generation
In this dissertation (titled: Exploring the Synergies between Transfer in Reinforcement Learning and Procedural Content Generation) we explore how the two research fields named in the title, namely Transfer in Reinforcement Learning (TRL) and Procedural Content Generation (PCG) can synergize togethe…
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Onderzoekers
In dit interdisciplinaire onderzoeksprogramma werken onderzoekers uit vijf verschillende disciplines met elkaar samen. Zij stellen zich hieronder (in het Engels) aan u voor.