Compressive Ptychography using Deep Image and Generative Priors

S. Barutcu, D. Gursoy, A. K. Katsaggelos,

ArXiv

Limited-Angle Computed Tomography with Deep Image and Physics Priors

S. Barutcu, S. Aslan, A. K. Katsaggelos, D. Gursoy,

Nature - Scientific Reports

Fast simulations in Computer-Generated Holograms for Binary data storage.

Manuel Ballester, Florian Schiffers, Zihao Wang, Hamid Hasani, Lionel Fiske, Prasan Shedligeri, Jack Tumblin, Florian Willomitzer, Aggelos K. Katsaggelos, Oliver Cossairt,

Conference paper at Computational Optical Sensing and Imaging (OSA)

Regularization for Undersampled Ptychography

P. Shedligeri, S. Barutcu, F. Schiffers, P. Ruiz, A. K. Katsaggelos, O. Cossairt,

Computational Optical Sensing and Imaging

Improving Acquisition Speed of X-Ray Ptychography through Spatial Undersampling and Regularization

P. Shedligeri, S. Barutcu, F. Schiffers, P. Ruiz, A. K. Katsaggelos, O. Cossairt,

Proc. of the IEEE Conf. on Image Processing

Reinforcement Learning for Adaptive Video Compressive Sensing

S. Lu, X. Yuan, A. K. Katsaggelos, W. Shi,

Removing Blocking Artifacts in Video Streams Using Event Cameras

H. H. Chopp, S. Banerjee, O. Cossairt, A. K. Katsaggelos,

arxiv.org/abs/2105.05973

Adaptive Illumination based Depth Sensing using Deep Learning

Q. Dai, F. Li, O. Cossairt, A. K. Katsaggelos,

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

X. Yuan, D. J. Brady, A. K. Katsaggelos,

Snapshot Compressive Imaging: Theory, Algorithms, and Applications

X. Yuan, D. J. Brady, A. K. Katsaggelos,

IEEE Signal Processing Magazine, vol. 38, no. 2, pp. 65-88

SkinScan: Low-Cost 3D-Scanning for Dermatologic Diagnosis and Documentation

M. A. Nau, F. Schiffers, Y. Li, B. Xu, A. Maier, J. Tumblin, M. Walton, A. K. Katsaggelos, F. Willomitzer, O. Cossairt,

Automated Atrial Fibrillation Detection using a Hybrid CNN-LSTM Network on Imbalanced ECG Datasets

G. Petmezas, K. Haris, L. Stefanopoulos, V. Kilintzis, A. Tzavelis, J. A. Rogers, A. K. Katsaggelos, N. Maglaveras,

Biomedical Signal Processing and Control, Volume 63

E3D: Event-Based 3D Shape Reconstruction

A.Baudron, Z. W. Wang, O. Cossairt, A. K. Katsaggelos,

2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network

H. Wei, F. Schiffers, T. Würfl, D. Shen, D. Kim, A. K. Katsaggelos, O. Cossairt,

Quadtree Driven Lossy Event Compression

S. Banerjee, Z. W. Wang, H. H. Chopp, O. Cossairt, A. K. Katsaggelos,

DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large US Clinical Dataset

R. M. Wehbe, J. Sheng, S. Dutta, S. Chai, A. Dravid, S. Barutcu, Y. Wu, D. R. Cantrell, N. Xiao, B. D. Allen, G. A. MacNealy, H. Savas, R. Agrawal, N. Parekh, A. K. Katsaggelos,

Radiology

Super Gaussian Priors for Blind Color Deconvolution of Histological Images

F. Pérez-Bueno, M. Vega, V. Naranjo, R. Molina, A. K. Katsaggelos,

2020 IEEE Int. Conf. on Image Processing (ICIP)

Interpretation of Brain Morphology in Association to Alzheimer’s Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

E. Azcona, P. Besson, Y. Wu, A. Punjabi, A. Martersteck, A. Dravid, T. B. Parrish, S. K. Bandt, A. K. Katsaggelos,

Proceedings of International Workshop on Shape in Medical Imaging (ShapeMI) in Conjunction with MICCAI 2020. LNCS, vol 12474. Springer

Simultaneous 3D X-Ray Ptycho-Tomography with Gradient Descent

S. Barutcu, P. Ruiz, F. Schiffers, S. Aslan, D. Gursoy, O. Cossairt, A. K. Katsaggelos,

IEEE Int. Conf. on Image Processing (ICIP)

Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors

F. Pérez-Bueno, M. Vega, J. Mateos, R. Molina, A. K. Katsaggelos,

Sensors 2020, 20, 5308

A single video super-resolution GAN for multiple downsampling operators based on pseudo-inverse image formation models

S. López-Tapia, A. Lucas, R. Molina, A. K. Katsaggelos,

Digital Signal Processing, Volume 104

Joint Filtering of Intensity Images and Neuromorphic Events for High-Resolution Noise-Robust Imaging

Z. W. Wang, P. Duan, O. Cossairt, A. K. Katsaggelos, T. Huang, B. Shi,

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Temporal capsule networks for video motion estimation and error concealment

A. Sankisa, A. Punjabi, A. K. Katsaggelos,

SIViP 14, 1369–1377

A TV-based image processing framework for blind color deconvolution and classification of histological images

F. Pérez-Bueno, M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos,

Digital Signal Processing, Volume 101

Knowledge Tracing to Model Learning in Online Citizen Science Projects

K. Crowston, C. S. Østerlund, T. K. Lee, C. Jackson, M. Harandi, S. Allen, S. Bahaadini, S. Coughlin, A. K. Katsaggelos, S. L. Larson, N. Rohani, J. R. Smith, L. Trouille, M. Zevin,

IEEE Transactions on Learning Technologies, vol. 13, no. 1, pp. 123-134

Examining the Benefits of Capsule Neural Networks

A. Punjabi, J. Schmid, A. K. Katsaggelos,

Fully Automatic Blind Color Deconvolution of Histological Images Using Super Gaussians

F. Pérez-Bueno, M. Vega, V. Naranjo, R. Molina, A. K. Katsaggelos,

2020 28th European Signal Processing Conference (EUSIPCO)

Gated Recurrent Networks for Video Super Resolution

S. López-Tapia, A. Lucas, R. Molina, A. K. Katsaggelos,

2020 28th European Signal Processing Conference (EUSIPCO)

Variational Bayesian Blind Color Deconvolution of Histopathological Images

N. Hidalgo-Gavira, J. Mateos, M. Vega, R. Molina, A. K. Katsaggelos,

IEEE Transactions on Image Processing, vol. 29, pp. 2026-2036

Self-Supervised Fine-tuning for Image Enhancement of Super-Resolution Deep Neural Networks

A. Lucas, S. Lopez-Tapia, R. Molina, A.K. Katsaggelos,

arXiv preprint arXiv:1912.12879

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

Q. Dai, H. Chopp, E. Pouyet, O. Cossairt, M. Walton, A. K. Katsaggelos,

IEEE Trans. on Multimedia, vol. 22(10), pp. 2564-2578

Neuroimaging modality fusion in Alzheimer’s classification using convolutional neural networks

A. Punjabi, A. Martersteck, Y. Wang, T. B. Parrish, A. K. Katsaggelos,

PLOS ONE

Teaching citizen scientists to categorize glitches using machine learning guided training

C. B. Jackson, C. S. Østerlund, K. Crowston, M. Harandi, S. Allen, S. Bahaadini, S. Coughlin, V. Kalogera, A. K. Katsaggelos, S. L. Larson, N. Rohani, J. R. Smith, L. Trouille, M. Zevin,

Computers in Human Behavior, Volume 105

Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO

P. Morales-Álvarez, P. Ruiz, S. Coughlin, R. Molina, A.K. Katsaggelos,

Under review at IEEE Transactions on Pattern Analysis and Machine Intelligence, arXiv preprint arXiv:1911.01915

DeepBinaryMask: Learning a binary mask for video compressive sensing

M. Iliadis, L. Spinoulas , A. K. Katsaggelos,

Digital Signal Processing, Volume 96

Optical Flow Prediction for Blind and Non-Blind Video Error Concealment Using Deep Neural Networks

A. Sankisa, A. Punjabi, A. K. Katsaggelos,

International Journal of Multimedia Data Engineering and Management (IJMDEM)

GAN-Based Video Super-Resolution with Direct Regularized Inversion of the Low-Resolution Formation Model

S. Lopez-Tapia, A. Lucas, R. Molina, A.K. Katsaggelos,

IEEE 2019 International Conference on Image Processing (ICIP)

Efficient Fine-tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging Problems

A. Lucas, S. Lopez-Tapia, R. Molina, A.K. Katsaggelos,

IEEE 2019 International Conference on Image Processing (ICIP)

Visible transmission imaging of watermarks by suppression of occluding text or drawings

P. Ruiz, O. Dill, G. Raju, O. Cossairt, M. Walton, A. K. Katsaggelos,

Digital Applications in Archaeology and Cultural Heritage, vol.15, e00121

An Adaptive Video Acquisition Scheme for Object Tracking

S. Banerjee, J. G. Serra, H. Chopp, O. Cossairt, A. K. Katsaggelos,

2019 27th European Signal Processing Conference (EUSIPCO)

Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation Model

S. Lopez-Tapia, A. Lucas, R. Molina, A.K. Katsaggelos,

2019 27th European Signal Processing Conference (EUSIPCO)

Spatially Adaptive Losses for Video Super-resolution with GANs

X. Wang, A. Lucas, S. L. Tapia, X. Wu, R. Molina, A. K. Katsaggelos,

IEEE Int. Conf. on Acoustics, Speech and Signal Processing

Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning

S. Coughlin, S. Bahaadini, N. Rohani, M. Zevin, O. Patane, M. Harandi, C. Jackson, V. Noroozi, S. Allen, J. Areeda, M. Coughlin, P. Ruiz, C. P. L. Berry, K. Crowston, A. K. Katsaggelos, A. Lundgren, C. Østerlund, J. R. Smith, L. Trouille, V. Kalogera,

Physical Review D, vol. 99, 082002

Learning from crowds with variational Gaussian processes

P. Ruiz, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos,

Pattern Recognition, vol. 88, pp. 298-311

Variational EM Method for Blur Estimation using the Spike-and-Slab Image Prior

J. G. Serra, J. Mateos, R. Molina, A. K. Katsaggelos,

Digital Signal Processing

Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

A. Lucas, S. Lopez-Tapia, R. Molina, A. K. Katsaggelos,

IEEE Trans. on Image Processing

Scalable and Efficient Learning from Crowds with Gaussian Processes

P. Morales-Álvarez, P. Ruiz, R. Santos-Rodríguez, R. Molina, A. K. Katsaggelos,

Information Fusion

Computational multifocal microscopy

K. He, Z. Wang, X. Huang, X. Wang, S. Yoo, et al.,

Biomedical Optics Express, vol. 9(12), pp. 6477-6496

Variational Gaussian process for multisensor classification problems

N. Rohani, P. Ruiz, R. Molina, A. K. Katsaggelos,

Pattern Recognition Letters

Design and simulation of a snapshot multi-focal interferometric microscope

K. He, X. Huang, X. Wang, S. Yoo, P. Ruiz, et al.,

Optics express, vol. 26(21), pp. 27381-27402