26 search results for “deep learning” in the Public website
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Deep learning for visual understanding
With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.
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Exploring deep learning for multimodal understanding
This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.
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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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Exploring Images With Deep Learning for Classification, Retrieval and Synthesis
In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.
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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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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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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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AI-SUPPORTED SYNTHESIS OF SHEPARD-RISSET FREQUENCY SETS
Implementation of the new sound synthesis and analysis method in music composition.
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Julia Wasala
Science
j.wasala@liacs.leidenuniv.nl | +31 71 527 4799
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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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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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Ana Cristina Arcos Marin
Science
a.c.arcos.marin@liacs.leidenuniv.nl | +31 71 527 2727
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Zihao Yuan
Science
z.yuan@cml.leidenuniv.nl | +31 71 527 2727
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Michael Lew
Science
m.s.lew@liacs.leidenuniv.nl | +31 71 527 7034
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Aske Plaat
Science
a.plaat@liacs.leidenuniv.nl | +31 71 527 7065
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Alan Kai Hassen
Science
a.k.hassen@liacs.leidenuniv.nl | +31 71 527 4799
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Fons Verbeek
Science
f.j.verbeek@liacs.leidenuniv.nl | +31 71 527 5773
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Spectral imaging and tomographic reconstruction methods for industrial applications
Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.
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Aspects of the analysis of cell imagery: from shape to understanding
In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope.
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André Mesquita Fery Antunes
Science
a.r.mesquita.fery.antunes@liacs.leidenuniv.nl | +31 71 527 2727
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Guilherme Perin
Science
g.perin@liacs.leidenuniv.nl | +31 71 527 2727
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To explore the drug space smarter: Artificial intelligence in drug design for G protein-coupled receptors
Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…
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Lecture: Aja Huang (Google DeepMind) on AlphaGo
How did Google’s computer programme AlphaGo become so good at board game Go that it could defeat the world champion? On June 29, developer Aja Huang will speak about this during a lecture in the Gorlaeus building.
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Aja Huang: 'The power of AlphaGo is in the use of neural networks'
How did Google's computer programme AlphaGo become so powerful? On June 29, developer Aja Huang elaborated on this during a lecture in the Gorlaeus building.
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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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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.