Concept

Object detection

Related publications (288)

Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translation

State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data. However, these methods require the training of one specific model for every ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Deep neural networks for plasma tomography with applications to JET and COMPASS

Olivier Sauter, Yiming Li, Ambrogio Fasoli, Basil Duval, Jonathan Graves, Duccio Testa, Patrick Blanchard, Alessandro Pau, Federico Alberto Alfredo Felici, Cristian Sommariva, Antoine Pierre Emmanuel Alexis Merle, Haomin Sun, Michele Marin, Henri Weisen, Richard Pitts, Yann Camenen, Jan Horacek, Javier García Hernández, Marco Wischmeier, Nicola Vianello, Mikhail Maslov, Federico Nespoli, Yao Zhou, Davide Galassi, Antonio José Pereira de Figueiredo, Hamish William Patten, Samuel Lanthaler, Emiliano Fable, Francesca Maria Poli, Daniele Brunetti, Anna Teplukhina, Alberto Mariani, Kenji Tanaka, Bernhard Sieglin, Otto Asunta, Gergely Papp, Leonardo Pigatto

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural network ...

2019

Tampered Speaker Inconsistency Detection with Phonetically Aware Audio-visual Features

Sébastien Marcel

The recent increase in social media based propaganda, i.e., ‘fake news’, calls for automated methods to detect tampered content. In this paper, we focus on detecting tampering in a video with a person speaking to a camera. This form of manipulation is easy ...

2019

Caries Detection with Near-Infrared Transillumination Using Deep Learning

Henry Markram, Taylor Howard Newton, Francesco Casalegno

Dental caries is the most prevalent chronic condition worldwide. Early detection can significantly improve treatment outcomes and reduce the need for invasive procedures. Recently, near-infrared transillumination (TI) imaging has been shown to be effective ...

2019

DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

Jean-Philippe Thiran, Hazim Kemal Ekenel, Saleh Baghersalimi

Recent state-of-the-art methods for skin lesion segmentation are based on convolutional neural networks (CNNs). Even though these CNN-based segmentation approaches are accurate, they are computationally expensive. In this paper, we address this problem and ...

2019

Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images

Pascal Fua, Mathieu Salzmann, Carlos Joaquin Becker, Róger Bermúdez Chacón, Okan Altingövde

We present an Unsupervised Domain Adaptation strategy to compensate for domain shifts on Electron Microscopy volumes. Our method aggregates visual correspondences—motifs that are visually similar across different acquisitions—to infer changes on the parame ...

2019

Target Detection with Deep Learning in Polarimetric Imaging

Selman Ergünay, Yusuf Leblebici, Süha Kagan Köse

Polarimetric imaging techniques demonstrate enhanced capabilities in advanced object detection tasks with their capability to discriminate man-made objects from natural background surfaces. While spectral signatures carry information only about material pr ...

SPIE-INT SOC OPTICAL ENGINEERING2018

Beyond Sharing Weights for Deep Domain Adaptation

Pascal Fua, Mathieu Salzmann, Artem Rozantsev

The performance of a classifier trained on data coming from a specific domain typically degrades when applied to a related but different one. While annotating many samples from the new domain would address this issue, it is often too expensive or impractic ...

2018

Hardware Implementation of a Smart Camera with Keypoint Detection and Description

Selman Ergünay, Yusuf Leblebici

Feature detection and description constitute important steps of many computer vision applications such as object detection and panorama stitching. Since those steps are computationally heavy, they might occupy significant portion of the full operation. Alt ...

IEEE2018

Variational Methods for Human Modeling

Timur Bagautdinov

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

EPFL2018

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