AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

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.

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

This work introduces DiGress, a discrete denoising diffusion model for generating graphs with categorical node and edge attributes. Our model utilizes a discrete diffusion process that progressively edits graphs with noise, through the process of adding or ...

In the context of automatic visual inspection of infrastructures by drones, Deep Learning (DL) models are used to automatically process images for fault diagnostics. While explainable Artificial Intelligence (AI) algorithms can provide explanations to asse ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

Snowfall is an essential component of the hydrological cycle, as it is involved in most precipitation on Earth, either directly as snow falling to the ground or indirectly as rain melted from snow. At the same time, the ice phase of clouds and precipitatio ...

Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...

This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Chat with Graph Search

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

DiGress: Discrete Denoising diffusion for graph generation

Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection

Automated Human Motion Analysis and Synthesis

Snowfall microphysics: a dual-frequency and Doppler spectral radar perspective

MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

Text as a Richer Source of Supervision in Semantic Segmentation Tasks

Transformer Models for Vision

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Dense Image-based Predictions for Comics Analysis