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Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression [article]

Elvira Fleig, Jonas Geistert, Erik Bochinski, Rolf Jongebloed, Thomas Sikora
2022 arXiv   pre-print
Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations, applicable to many use-cases in image processing.  ...  Recent works for image compression indicate that compression of images based on SMoE models can provide competitive performance to the state-of-the-art.  ...  INTRODUCTION The Steered Mixture-of-Experts (SMoE) approach has been first presented as a promising regression framework for coding images [1] [2] [3] [4] [5] and has since expanded to other application  ... 
arXiv:2207.12348v1 fatcat:xhrl5uxrsjd55nnhwhbdxjpcyy

Steered Mixture-of-Experts for Light Field Images and Video: Representation and Coding

Ruben Verhack, Sikora Thomas, Glenn Van Wallendael, Peter Lambert
2019 IEEE transactions on multimedia  
We propose a novel coding framework for higher-dimensional image modalities, called Steered Mixture-of-Experts (SMoE).  ...  We introduce the theory of SMoE and illustrate its application for 2-D images, 4-D LF images, and 5-D LF video.  ...  Example: 1-D Steered Mixture-of-Experts (SMoE) For illustration purposes, Fig. 2 depicts a SMoE regression of samples from a 1-D image scan line.  ... 
doi:10.1109/tmm.2019.2932614 fatcat:2nuvguaeorguxlkhqir6yzi27e

Table of Contents

2019 2019 Data Compression Conference (DCC)  
for Coding Images Using Steered Mixtures-of-Experts ................................................................................................................ 359 Rolf Jongebloed, Erik Bochinski,  ...  ................................................................................................................. 349 Mor Goren and Ram Zamir Tel Aviv University Quantized and Regularized Optimization  ... 
doi:10.1109/dcc.2019.00007 fatcat:523crdy42jdypjynpohc6dt5ba

Front Matter: Volume 10752

Andrew G. Tescher
2018 Applications of Digital Image Processing XLI  
algorithm for orthogonal transformations [10752-100] 10752 2S A regularization algorithm for registration of deformable surfaces [10752-101] 10752 2T Image dehazing using total variation regularization  ...  These two-number sets start with 00, 01, 02, 03, 04, Terms of Use: https://www.spiedigitallibrary.org/terms-of-use An algorithm for selecting face features using deep learning techniques based on autoencoders  ...  Three dimensional reconstruction using a lenslet light field camera [10752-9] 10752 0A Canonical 3D object orientation for interactive light-field visualization [10752-10] 10752 0B Steered mixture-of-experts  ... 
doi:10.1117/12.2514600 fatcat:krclqvyguvfwxk5k4snmesnroq

Highly parallel steered mixture-of-experts rendering at pixel-level for image and light field data

Vasileios Avramelos, Ruben Verhack, Ignace Saenen, Glenn Van Wallendael, Bart Goossens, Peter Lambert
2018 Journal of Real-Time Image Processing  
A novel image approximation framework called Steered Mixture-of-Experts (SMoE) was recently presented.  ...  SMoE has multiple applications in coding, scale-conversion, and general processing of image modalities.  ...  Such a scheme does fit multi-threading architectures, but is less suited for massively parallel architectures. 3 Steered Mixture-of-Experts Introduction Steered Mixture-of-Experts (SMoE) is a novel framework  ... 
doi:10.1007/s11554-018-0843-3 fatcat:pcubeilcizeu5ezx52wnv2udvi

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 6110-6122 An Optimized Quantization Constraints Set for Image Restoration and its GPU Implementation.  ...  ., +, TIP 2020 3039-3051 Biased Mixtures of Experts: Enabling Computer Vision Inference Under Data Transfer Limitations.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Segmentation and Feature Extraction in Medical Imaging: A Systematic Review

Chiranji Lal Chowdhary, D.P. Acharjya
2020 Procedia Computer Science  
In this paper, authors survey on various segmentation and feature extraction methods in medicinal images used for preprocessing.  ...  In this paper, authors survey on various segmentation and feature extraction methods in medicinal images used for preprocessing.  ...  The authors also provide a shortcut for better segmentation. Some commonly used semi-automatic methods are intelligent scissors, user steered image segmentation, and fuzzy connectedness.  ... 
doi:10.1016/j.procs.2020.03.179 fatcat:5oarv6vyjfdsjpoectpeiie2fe

A Survey of End-to-End Driving: Architectures and Training Methods [article]

Ardi Tampuu, Maksym Semikin, Naveed Muhammad, Dmytro Fishman and Tambet Matiisen
2020 arXiv   pre-print
Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the context of perception.  ...  Interpretability and safety are discussed separately, as they remain challenging for this approach.  ...  ACKNOWLEDGMENTS The authors would like to thank Hannes Liik for fruitful discussions.  ... 
arXiv:2003.06404v1 fatcat:ekb4g7waa5fyldfaxhgnb3a5xm

ICASSP 2020 Table of Contents

2020 ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
TOPOLOGY OPTIMIZATION FOR IMAGE DENOISING Wengtai Su, National Tsing Hua University, Taiwan; Gene Cheung, Richard P.  ...  , Germany IVMSP-P12.5: NON-EXPERTS OR EXPERTS?  ...  ........................ 2508 USING DEEP LEARNING Jun-Ho Choi, Jun-Hyuk Kim, Jong-Seok Lee, Yonsei University, Korea (South) IVMSP-P8.5: SUB-DIP: OPTIMIZATION ON A SUBSPACE WITH DEEP IMAGE PRIOR ......  ... 
doi:10.1109/icassp40776.2020.9054406 fatcat:6h7hh2hxhne4pbmphharu2et2m

Paraglide: Interactive Parameter Space Partitioning for Computer Simulations [article]

Steven Bergner, Michael Sedlmair, Sareh Nabi, Ahmed Saad, Torsten Möller
2011 arXiv   pre-print
studies underlining the usefulness of our approach.  ...  We first analyzed current practices of six domain experts and derived a set of design requirements, then engaged in a longitudinal user-centered design process, and finally conducted three in-depth case  ...  [28] identified further uses for model exploration, algorithm experimentation, and performance optimization.  ... 
arXiv:1110.5181v1 fatcat:7c3p75wnjbhbbhu5uqnxjjkdsm

Generative Adversarial Networks and Other Generative Models [article]

Markus Wenzel
2022 arXiv   pre-print
Though this chapter focuses on GANs that are meant for image generation and image analysis, the adversarial training paradigm itself is not specific to images, and also generalizes to tasks in image analysis  ...  Examples of architectures for image semantic segmentation and abnormality detection will be acclaimed, before contrasting GANs with further generative modeling approaches lately entering the scene.  ...  Acknowledgments I thank my colleague at the Fraunhofer Institute for Digital Medicine MEVIS, Till Nicke, for his thorough review of the chapter and many valuable suggestions for improvements.  ... 
arXiv:2207.03887v1 fatcat:n5vqqmkbpfc5zbwsgbvcazz7va

2021 Index IEEE Transactions on Cybernetics Vol. 51

2021 IEEE Transactions on Cybernetics  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Image sequences A Three-Way Optimization Technique for Noise Robust Moving Object Detection Using Tensor Low-Rank Approximation, l 1/2 , and TTV Regularizations.  ... 
doi:10.1109/tcyb.2021.3139447 fatcat:myjx3olwvfcfpgnwvbuujwzyoi

Neuro-fuzzy Logic in Signal Processing for Communications: From Bits to Protocols [chapter]

Ana Pérez-Neira, Miguel A. Lagunas, Antoni Morell, Joan Bas
2006 Lecture Notes in Computer Science  
From signal processing applications, which process bits at the physical layer in order to face complicate problems of non-Gaussian noise, to practical and robust implementations of these systems and up  ...  The ability for modeling uncertainty with a reasonable trade-off between complexity and model accuracy, makes fuzzy logic a promising tool.  ...  Fig. 15 shows the results of the unsupervised classifiers: FACM, ML, W and FW for each of the 15 temporal mixtures.  ... 
doi:10.1007/11613107_2 fatcat:5lwvxq5mfjgt7ebmzv4oskh3my

Applications and Techniques for Fast Machine Learning in Science [article]

Allison McCarn Deiana, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini (+74 others)
2021 arXiv   pre-print
The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for  ...  This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions.  ...  Each node is tagged with the quantization of its inputs, parameters (weights and activations), and outputs to enable quantization-aware optimizations and the mapping to backend primitives optimized for  ... 
arXiv:2110.13041v1 fatcat:cvbo2hmfgfcuxi7abezypw2qrm

Discriminative Transfer Learning for General Image Restoration

Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Scholkopf, Michael Hirsch
2018 IEEE Transactions on Image Processing  
However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images).  ...  In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration.  ...  Diversity of data likelihood The seminal work of fields-of-experts (FoE) [30] generalizes the form of filter response based regularizers in the objective function given in Eq. 1.  ... 
doi:10.1109/tip.2018.2831925 pmid:29993740 fatcat:prsa74c75jhyhnufmzbkykhqza
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