Dynamic and Scalable Large Scale Image Reconstruction

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.

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Thanks to recent advancements in image processing and deep learning techniques, visual surface inspection in production lines has become an automated process as long as all the defects are visible in a single or a few images. However, it is often necessary ...

In this work, we resolve a big challenge that most current image quality metrics (IQMs) are unavailable across different image contents, especially simultaneously coping with natural scene (NS) images or screen content (SC) images. By comparison with exist ...

State of the art content-based image retrieval algorithms owe their excellent performance to the rich semantics encoded in the deep activations of a convolutional neural network. The difference between these algorithms lies mostly in how activations are co ...

With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia. Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...

Ongoing advances in imaging techniques create new demands regarding the analysis of images in medicine and biology. Image segmentation is a key step of many image analysis pipelines and its proper execution is a particularly challenging task. This thesis i ...

A versatile method to automatically classify ice particle habit from various airborne optical array probes is presented. The classification is achieved using a multinomial logistic regression model. For each airborne probe, the model determines the particl ...

Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methods have proposed to fine-tune pre-trained networks using im ...

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suf ...

Multimedia data with associated semantics is omnipresent in today’s social online platforms in the form of keywords, user comments and so forth. This article presents a statistical framework designed to infer knowledge in the imaging domain from the semant ...

Terrestrial imagery found in public databases is an alternative and complementary data source for environmental studies. Compared to usual data source, such as airborne images, terrestrial pictures may have higher temporal and spatial resolutions. They are ...

We propose a robust method for registering high oblique images of landscapes. Typically, an input image can be registered by matching it against a set of registered images of the same location. While this has been shown to work very well for images of popu ...

Content Based Image Retrieval (CBIR) has gained a lot of interest over the last two decades. The need to search and retrieve images from databases, based on information (“features”) extracted from the image itself, is becoming increasingly important. CBIR ...

This work extends previous studies on using EEG decoding for automatic image retrieval. We propose an iterative way to integrate the information obtained from the EEG decoding and image processing methods. In the light of real-world BCI applications, we de ...

The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...

Finding relations between image semantics and image characteristics is a problem of long standing in computer vision and related fields. Despite persistent efforts and significant advances in the field, today’s computers are still strikingly unable to achi ...

The ability to automatically find objects of interest in images is useful in the areas of compression, indexing and retrieval, re-targeting, and so on. There are two classes of such algorithms – those that find any object of interest with no prior knowledg ...

We present a novel image-based method to measure the on-chip microfluidic pressure and flow rate simultaneously by using the integrated optofluidic membrane interferometers (OMIs). The device was constructed with two layers of structured polydimethylsiloxa ...

Dynamic and Scalable Large Scale Image Reconstruction

Chat with Graph Search

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Defect segmentation for multi-illumination quality control systems

Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances

Deep Feature Factorization For Content-Based Image Retrieval And Localization

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

A Versatile Method for Ice Particle Habit Classification Using Airborne Imaging Probe Data

Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation

Shapes from Pixels

An image-based method to automatically propagate bony landmarks: application to computational spine biomechanics

Semantic-Improved Color Imaging Applications: It Is All About Context

Registration of single landscape photographs with 3D landscape models

Pose Estimation of Web-Shared Landscape Pictures

Low Complexity Image Recognition Algorithms for Handheld devices

Iterative EEG-based Natural Image Search under RSVP

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Semantic Awareness for Automatic Image Interpretation

Finding Objects of Interest in Images using Saliency and Superpixels

Optofluidic membrane interferometer: An imaging method for measuring microfluidic pressure and flow rate simultaneously on a chip