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A universal image coding approach using sparse steered Mixture-of-Experts regression

Ruben Verhack, Thomas Sikora, Lieven Lange, Glenn Van Wallendael, Peter Lambert
2016 2016 IEEE International Conference on Image Processing (ICIP)  
A universal image coding approach using sparse steered Mixture-of-Experts regression. ABSTRACT Our challenge is the design of a "universal" bit-efficient image compression approach.  ...  To this end, we introduce a sparse Mixture-of-Experts regression approach for coding images in the pixel domain.  ...  In this paper, we introduce a sparse Steered Mixture-of-Experts (SMoE) representation for images that provide local adaptability with global support.  ... 
doi:10.1109/icip.2016.7532737 dblp:conf/icip/VerhackSLWL16 fatcat:b2fxpw5tnfdeddrql5jdoghz7u

Steered mixture-of-experts for light field coding, depth estimation, and processing

Ruben Verhack, Thomas Sikora, Lieven Lange, Rolf Jongebloed, Glenn Van Wallendael, Peter Lambert
2017 2017 IEEE International Conference on Multimedia and Expo (ICME)  
The proposed framework, called Steered Mixture-of-Experts (SMoE), enables a multitude of processing tasks on light fields using a single unified Bayesian model.  ...  This allows for "blind" light field processing and classification Index Termslight field coding, depth estimation, light field representations, mixture-of-experts, mixture models  ...  STEERED MIXTURE-OF-EXPERTS Introduction In the Steered Mixture-of-Experts (SMoE) framework, the underlying stochastic process of the amplitudes are modeled as a N -D multi-modal Mixture Model with K  ... 
doi:10.1109/icme.2017.8019442 dblp:conf/icmcs/VerhackSLJWL17 fatcat:w6c5ugxwv5fjti4l4canoshbou

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).  ...  Index Terms-Mixture of experts, light fields, mixture models, sparse representation, bayesian modeling.  ...  of a Mixture-of-Experts with one layer for regression.  ... 
doi:10.1109/tmm.2019.2932614 fatcat:2nuvguaeorguxlkhqir6yzi27e

Steered mixture-of-experts for light field video coding

Glenn Van Wallendael, Ruben Verhack, Peter Lambert, Thomas Sikora, Vasileios Avramelos, Ignace Saenen, Andrew G. Tescher
2018 Applications of Digital Image Processing XLI  
Steered Mixture-of-Experts (SMoE) is a novel framework for representing multidimensional image modalities.  ...  We evaluate the coding performance of SMoE models of light field video, a 5D image modality, i.e. time, two angular, and two spatial dimensions.  ...  The computational resources (STEVIN Supercomputer Infrastructure) and services used in this work were kindly provided by Ghent University, the Flemish Supercomputer Center (VSC), the Hercules Foundation  ... 
doi:10.1117/12.2320563 fatcat:4irrbdhi5bactjrx4u4ak5tcli

Spatial Accuracy Assessment and Integration of Global Land Cover Datasets

Nandin-Erdene Tsendbazar, Sytze de Bruin, Steffen Fritz, Martin Herold
2015 Remote Sensing  
See et al. [9] created hybrid GLC maps using Geo-Wiki reference data within a geographically weighted kernel approach [16] .  ...  This approach was improved and applied to a larger area to create an integrated pan-tropical biomass map using multiple reference datasets [14] .  ...  We are grateful to the experts involved in the generation of the reference datasets for their valuable input.  ... 
doi:10.3390/rs71215804 fatcat:qwqamg5zy5hj5hnoplwa63zxma

GRACE: A Visual Comparison Framework for Integrated Spatial and Non-Spatial Geriatric Data

Adrian Maries, Nathan Mays, Megan Olson Hunt, Kim F. Wong, William Layton, Robert Boudreau, Caterina Rosano, G. Elisabeta Marai
2013 IEEE Transactions on Visualization and Computer Graphics  
In addition to the domain analysis and design description, we demonstrate the usefulness of this approach on two case studies.  ...  The visual analysis framework blends medical imaging, mathematical analysis and interactive visualization techniques, and includes the adaptation of Sparse Partial Least Squares and iterated Tikhonov Regularization  ...  ACKNOWLEDGMENTS This work was supported by NIH R01-AG029232, NSF IIS-0952720, and by a University of Pittsburgh Small Multidisciplinary Grant.  ... 
doi:10.1109/tvcg.2013.161 pmid:24051859 pmcid:PMC4423600 fatcat:mtnriqquurcwhpiqixnhdcxzxy

4-D Epanechnikov Mixture Regression in Light Field Image Compression

Boning Liu, Yan Zhao, Xiaomeng Jiang, Shigang Wang, Jian Wei
2021 IEEE transactions on circuits and systems for video technology (Print)  
of the pseudo video sequence of light field images, (3) using 4-D adaptive model selection for the optimal number of models, and (4) employing a linear function-based reconstruction according to the content  ...  With the emergence of light field imaging in recent years, the compression of its elementary image array (EIA) has become a significant problem.  ...  In addition to the algorithms implemented under HEVC, the research on image coding has also expanded to kernel regression frameworks such as the Steered Mixture-of-Experts (SMoE), in which the Gaussian  ... 
doi:10.1109/tcsvt.2021.3104575 fatcat:ze3ixfenlzedvngqg73ams4wuq

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 2507-2521 Biased Mixtures of Experts: Enabling Computer Vision Inference Under Data Transfer Limitations.  ...  Wang, X., +, TIP 2020 3039-3051 Biased Mixtures of Experts: Enabling Computer Vision Inference Under Data Transfer Limitations.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

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.  ...  In this paper we take a deeper look on the so called end-to-end approaches for autonomous driving, where the entire driving pipeline is replaced with a single neural network.  ...  A well-known late-fusion approach is ensembling, for example using Kalman filters [102] or mixture of experts [103] .  ... 
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.  ...  Wildes, York University, Taiwan; Chia-Wen Lin, National Tsing Hua University, Taiwan SS-L3.2: DEFENDING GRAPH CONVOLUTIONAL NETWORKS AGAINST ........................................................  ...  of Technology, China IVMSP-P2: IMAGE/VIDEO CODING I IVMSP-P2.1: LEARNED LOSSLESS IMAGE COMPRESSION WITH A HYPERPRIOR ............................................. 2158 AND DISCRETIZED GAUSSIAN MIXTURE  ... 
doi:10.1109/icassp40776.2020.9054406 fatcat:6h7hh2hxhne4pbmphharu2et2m

Human Automotive Interaction: Affect Recognition for Motor Trend Magazine's Best Driver Car of the Year [chapter]

Albert C. Cruz, Bir Bhanu, Belinda T. Le
2017 Emotion and Attention Recognition Based on Biological Signals and Images  
We propose a face detector that uniies state-of-the-art approaches and provides quality control for face detection results, called reference-based face detection.  ...  Existing methods to monitor a driver have included prediction from steering behavior, smart phone warning systems, gaze detection, and electroencephalogram.  ...  For the proposed approach, we use AIGF and do not compute a soft histogram. Local binary paterns Local binary paterns (LBP) encode local appearance as a microtexture code.  ... 
doi:10.5772/65684 fatcat:xlswoqvrfbdh5essbmzybikyyu

Discriminative Transfer Learning for General Image Restoration

Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Scholkopf, Michael Hirsch
2018 IEEE Transactions on Image Processing  
., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training.  ...  Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency.  ...  More expressive generative models include k-singular value decomposition (KSVD) [3] , convolutional sparse coding (CSC) [27] , [28] , [29] , fields of experts (FoE) [30] and expected patch log likelihood  ... 
doi:10.1109/tip.2018.2831925 pmid:29993740 fatcat:prsa74c75jhyhnufmzbkykhqza

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
This is a survey of autonomous driving technologies with deep learning methods.  ...  Almost at the same time, deep learning has made breakthrough by several pioneers, three of them (also called fathers of deep learning), Hinton, Bengio and LeCun, won ACM Turin Award in 2019.  ...  experts etc.); 3) When to fuse at given stages of feature representation in a NN.  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges [article]

Di Feng, Christian Haase-Schuetz, Lars Rosenbaum, Heinz Hertlein, Claudius Glaeser, Fabian Timm, Werner Wiesbeck, Klaus Dietmayer
2020 arXiv   pre-print
However, there is no general guideline for network architecture design, and questions of "what to fuse", "when to fuse", and "how to fuse" remain open.  ...  To this end, we first provide an overview of on-board sensors on test vehicles, open datasets, and background information for object detection and semantic segmentation in autonomous driving research.  ...  In contrast, the Mixture of Experts (MoE) approach explicitly models the weight of a feature map. It is first introduced in [159] for neural networks and then extended in [120] , [126] , [160] .  ... 
arXiv:1902.07830v4 fatcat:or6enjxktnamdmh2yekejjr4re

Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures

David K. Hammond, Eero P. Simoncelli
2008 IEEE Transactions on Image Processing  
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation.  ...  A third hidden variable selects between this oriented process and a nonoriented scale mixture of Gaussians process, thus providing adaptability to the local orientedness of the signal.  ...  Simple linear regression of this performance difference in dB versus average for the five test images used, with and two SP bands, gives a regression line with slope 1. 24 .  ... 
doi:10.1109/tip.2008.2004796 pmid:18972652 pmcid:PMC4144921 fatcat:fm2yuk4qpvd65m4qsb27ryjuhy
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