Search Results for author: Aggelos K. Katsaggelos

Found 26 papers, 8 papers with code

Compressive Ptychography using Deep Image and Generative Priors

no code implementations5 May 2022 Semih Barutcu, Doğa Gürsoy, Aggelos K. Katsaggelos

However, reconstructions with less number of scan points lead to imaging artifacts and significant distortions, hindering a quantitative evaluation of the results.

medXGAN: Visual Explanations for Medical Classifiers through a Generative Latent Space

no code implementations11 Apr 2022 Amil Dravid, Florian Schiffers, Boqing Gong, Aggelos K. Katsaggelos

Despite the surge of deep learning in the past decade, some users are skeptical to deploy these models in practice due to their black-box nature.

Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes

no code implementations22 Jan 2022 Amil Dravid, Florian Schiffers, Yunan Wu, Oliver Cossairt, Aggelos K. Katsaggelos

Generative Adversarial Networks (GANs) have shown promise in augmenting datasets and boosting convolutional neural networks' (CNN) performance on image classification tasks.

Classification Image Classification +1

Visual Explanations for Convolutional Neural Networks via Latent Traversal of Generative Adversarial Networks

1 code implementation29 Oct 2021 Amil Dravid, Aggelos K. Katsaggelos

Lack of explainability in artificial intelligence, specifically deep neural networks, remains a bottleneck for implementing models in practice.

Removing Blocking Artifacts in Video Streams Using Event Cameras

no code implementations12 May 2021 Henry H. Chopp, Srutarshi Banerjee, Oliver Cossairt, Aggelos K. Katsaggelos

In this paper, we propose EveRestNet, a convolutional neural network designed to remove blocking artifacts in videostreams using events from neuromorphic sensors.

Snapshot Compressive Imaging: Principle, Implementation, Theory, Algorithms and Applications

no code implementations7 Mar 2021 Xin Yuan, David J. Brady, Aggelos K. Katsaggelos

Via novel optical designs, the 2D detector samples the HD data in a {\em compressive} manner; following this, algorithms are employed to reconstruct the desired HD data-cube.

E3D: Event-Based 3D Shape Reconstruction

1 code implementation9 Dec 2020 Alexis Baudron, Zihao W. Wang, Oliver Cossairt, Aggelos K. Katsaggelos

We first introduce an event-to-silhouette (E2S) neural network module to transform a stack of event frames to the corresponding silhouettes, with additional neural branches for camera pose regression.

3D Reconstruction 3D Shape Reconstruction

Examining the Benefits of Capsule Neural Networks

no code implementations29 Jan 2020 Arjun Punjabi, Jonas Schmid, Aggelos K. Katsaggelos

Capsule networks are a recently developed class of neural networks that potentially address some of the deficiencies with traditional convolutional neural networks.

Self-supervised Fine-tuning for Correcting Super-Resolution Convolutional Neural Networks

no code implementations30 Dec 2019 Alice Lucas, Santiago Lopez-Tapia, Rafael Molina, Aggelos K. Katsaggelos

We apply our method on the problem of fine-tuning for unseen image formation models and on removal of artifacts introduced by GANs.

Image Enhancement Video Super-Resolution

A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models

no code implementations2 Jul 2019 Santiago López-Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos

The popularity of high and ultra-high definition displays has led to the need for methods to improve the quality of videos already obtained at much lower resolutions.

Video Super-Resolution

Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction

3 code implementations27 Dec 2018 Qiqin Dai, Henry Chopp, Emeline Pouyet, Oliver Cossairt, Marc Walton, Aggelos K. Katsaggelos

We propose an XRF image inpainting approach to address the issue of long scanning time, thus speeding up the scanning process while still maintaining the possibility to reconstruct a high quality XRF image.

Binarization Image Inpainting +1

Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

no code implementations14 Jun 2018 Alice Lucas, Santiago Lopez Tapia, Rafael Molina, Aggelos K. Katsaggelos

Finally, we show that our proposed model, the VSRResFeatGAN model, outperforms current state-of-the-art SR models, both quantitatively and qualitatively.

Image Restoration SSIM +1

DIRECT: Deep Discriminative Embedding for Clustering of LIGO Data

no code implementations7 May 2018 Sara Bahaadini, Vahid Noroozi, Neda Rohani, Scott Coughlin, Michael Zevin, Aggelos K. Katsaggelos

In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature extractor for clustering tasks.

Deep Multi-view Models for Glitch Classification

no code implementations28 Apr 2017 Sara Bahaadini, Neda Rohani, Scott Coughlin, Michael Zevin, Vicky Kalogera, Aggelos K. Katsaggelos

Non-cosmic, non-Gaussian disturbances known as "glitches", show up in gravitational-wave data of the Advanced Laser Interferometer Gravitational-wave Observatory, or aLIGO.

Classification General Classification +1

Compressive Holographic Video

no code implementations27 Oct 2016 Zihao Wang, Leonidas Spinoulas, Kuan He, Huaijin Chen, Lei Tian, Aggelos K. Katsaggelos, Oliver Cossairt

Compressive holography has been introduced as a method that allows 3D tomographic reconstruction at different depths from a single 2D image.


DeepBinaryMask: Learning a Binary Mask for Video Compressive Sensing

1 code implementation12 Jul 2016 Michael Iliadis, Leonidas Spinoulas, Aggelos K. Katsaggelos

In this paper, we propose a novel encoder-decoder neural network model referred to as DeepBinaryMask for video compressive sensing.

Compressive Sensing Video Compressive Sensing +1

Robust and Low-Rank Representation for Fast Face Identification with Occlusions

1 code implementation8 May 2016 Michael Iliadis, Haohong Wang, Rafael Molina, Aggelos K. Katsaggelos

In this paper we propose an iterative method to address the face identification problem with block occlusions.

Face Identification

Sparse Bayesian Methods for Low-Rank Matrix Estimation

no code implementations25 Feb 2011 S. Derin Babacan, Martin Luessi, Rafael Molina, Aggelos K. Katsaggelos

Recovery of low-rank matrices has recently seen significant activity in many areas of science and engineering, motivated by recent theoretical results for exact reconstruction guarantees and interesting practical applications.

Matrix Completion

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