Special Section Guest Editorial: Image and Video Compression Using Deep Neural Networks

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Synthetically grown high-quality single crystal diamond is an excellent base material for quantum photonics. Planar single crystal diamond substrates several square millimeters in size are nowadays commercially available. They can be precisely structured u ...

The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. This stan ...

Deep neural networks often fail to generalize when deployed in dynamic and unpredictable real-world environments, where data distributions at test time can differ significantly from those encountered during training. Since simulating all possible distribut ...

The use of immersive representations for digital media has been gaining growing attention fueled by novel applications such as virtual and augmented reality. Point clouds, which represent shapes as a collection of unconnected points in space with geometric ...

Previous methods for predicting room acoustic parameters and speech quality metrics have focused on the single-channel case, where room acoustics and Mean Opinion Score (MOS) are predicted for a single recording device. However, quality-based device select ...

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

This study introduces a Machine Learning (ML) approach for estimating the T2 spectrum and myelin water fraction (MWF) using multi-echo T2 (MET2) data from preclinical 7T Magnetic Resonance Imaging (MRI) scanners. ML methods have shown promise in MWF estima ...

Dynamic human energy expenditure (EE) consists of energy costs for resting metabolism, food digestion, physical activity, and thermoregulation. Currently, multiple models predict EE mainly concerning physical activity, thus, discarding other factors contri ...

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents that exchange information over a graph. In this setup, each agent receives data that might be generated from a different hypothesis (or state) t ...

The local integration of III-Vs on Si is relevant for a wide range of applications in electronics and photonics, since it combines a mature and established materials platform with desired physical properties such as a direct and tuneable bandgap and high m ...

Coded aperture cameras can be manufactured cheaply, have a very thin form-factor, and may be transparent and flexible, thus providing easy-to-integrate and compact image sensors. However, limitations in reconstructed image quality and resolution have imped ...

The European Space Agency's Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment o ...

In this paper, we aim to build the global convergence theory of encoder-only shallow Transformers under a realistic setting from the perspective of architectures, initialization, and scaling under a finite width regime. The difficulty lies in how to tackle ...

Ultrafast ultrasound (US) revolutionized biomedical imaging with its capability of acquiring full-view frames at over 1 kHz, unlocking breakthrough modalities such as shear-wave elastography and functional US neuroimaging. Yet, it suffers from strong diffr ...

Occupants' behavior is a major source of uncertainty for the optimal operation of building energy systems. The highly stochastic hot water use behavior of occupants has led to conservative operational strategies for hot water systems, that try to ensure oc ...

Under seismic actions, stone masonry buildings are prone to damage. To assess the severity of damaged masonry buildings and their failure modes, engineers connect these problems to surface crack features, such as the crack width and the extent of cracking. ...

We formulate as an inverse problem the construction of sparse parametric continuous curve models that fit a sequence of contour points. Our prior is incorporated as a regularization term that encourages rotation invariance and sparsity. We prove that an op ...

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this is ...

Current task-oriented dialog (TOD) systems mostly manage structured knowledge (e.g. databases and tables) to guide the goal-oriented conversations. However, they fall short of handling dialogs which also involve unstructured knowledge (e.g. reviews and doc ...

Special Section Guest Editorial: Image and Video Compression Using Deep Neural Networks

Chat with Graph Search

Micro- and nanofabrication techniques for single crystal diamond photonics

Automated Ensemble Multimodal Machine Learning for Healthcare

Adaptive Test-Time Learning Under Domain Shift: From Augmentation to Prolonged Adaptation

On quality assessment and learning-based compression of point clouds for conventional and DNA-based storage

Multi-Channel Mosra: Mean Opinion Score and Room Acoustics Estimation Using Simulated Data and A Teacher Model

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

In-Silico Trained AI for Enhanced T2Spectrum Imaging and Myelin Water Fraction Mapping in Preclinical 7T MRI

Dynamic personalized human body energy expenditure: Prediction using time series forecasting LSTM models

Self-Aware Social Learning Over Graphs

Review: III-V infrared emitters on Si: fabrication concepts, device architectures and down-scaling with a focus on template-assisted selective epitaxy

Toward High-Resolution Face Image Generation From Coded Aperture Camera

Euclid preparation XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

On the Convergence of Encoder-only Shallow Transformers

CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging

An occupant-centric control framework for balancing comfort, energy use and hygiene in hot water systems: A model-free reinforcement learning approach

Machine-learning for damage assessment of rubble stone masonry piers based on crack patterns

A novel fatigue life prediction methodology based on energy dissipation in viscoelastic materials (vol 152, 106457, 2021)

Coupled Splines for Sparse Curve Fitting

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

End-to-End Task-Oriented Dialog Modeling With Semi-Structured Knowledge Management