Spatially Adaptive Computation Time for Residual Networks
Figurnov M., Collins M. D., Zhu Y., Zhang L., Huang J., Vetrov D., Salakhutdinov R.
This paper proposes a deep learning architecture based on Residual Network that dynamically adjusts the number of executed layers for the regions of the image. This architecture is end-to-end trainable, deterministic and problem-agnostic. It is therefore applicable without any modifications to a wide range of computer vision problems such as image classification, object detection and image segmentation. We present experimental results showing that this model improves the computational efficiency of Residual Networks on the challenging ImageNet classification and COCO object detection datasets. Additionally, we evaluate the computation time maps on the visual saliency dataset cat2000 and find that they correlate surprisingly well with human eye fixation positions.
Cham: Springer, 2020
ICIAR 2020 was the 17th edition of the series of annual conferences on Image Analysis and Recognition, organized, this year, as a virtual conference due to the pandemic outbreak of Covid-19 affecting all the world, with an intensity never felt by the humanity in the last hundred years. These are difficult and challenging times, nevertheless ...
Added: October 1, 2020
Added: October 3, 2020
Computer Vision – ECCV 2020; 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XV
NY: Springer, 2020
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were ...
Added: October 28, 2020
Cham: Springer, 2020
The International Conference on Computer Vision and Graphics (ICCVG), organized since 2002, is the continuation of the International Conferences on Computer Graphics and Image Processing (GKPO), held in Poland every second year from 1990 to 2000. The main objective of ICCVG is to provide an environment for the exchange of ideas between researchers in the ...
Added: October 1, 2020
Piscataway: IEEE, 2020
2020 International Joint Conference on Neural Networks (IJCNN) held virtually, as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI) 2020. IJCNN 2020 is jointly organized by the IEEE Computational Intelligence Society (CIS) and the International Neural Network Society (INNS). For IJCNN 2020 (and when WCCI is organized in even-numbered years) IEEE CIS ...
Added: October 15, 2020
М.: Торус Пресс, 2018
The volume contains the abstracts of the 12th International Conference "Intelligent Data Processing: Theory and Applications". The conference is organized by the Russian Academy of Sciences, the Federal Research Center "Informatics and Control" of the Russian Academy of Sciences and the Scientific and Coordination Center "Digital Methods of Data Mining". The conference has being held biennially since 1989. It is one ...
Added: October 9, 2018
Deep neural networks and maximum likelihood search for approximate nearest neighbor in video-based image recognition
, Optical Memory and Neural Networks (Information Optics) 2017 Vol. 26 No. 2 P. 129-136
We analyzed the way to increase computational efficiency of video-based image recognition methods with matching of high dimensional feature vectors extracted by deep convolutional neural networks. We proposed an algorithm for approximate nearest neighbor search. At the first step, for a given video frame the algorithm verifies a reference image obtained when recognizing the previous ...
Added: June 30, 2017
Intelligent Data Processing 11th International Conference, IDP 2016, Barcelona, Spain, October 10–14, 2016, Revised Selected Papers
Switzerland: Springer, 2019
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Processing, IDP 2016, held in Barcelona, Spain, in October 2016. The 11 revised full papers were carefully reviewed and selected from 52 submissions. The papers of this volume are organized in topical sections on machine learning theory with applications; intelligent data processing in life ...
Added: February 8, 2020
Foundations of Intelligent Systems. 25th International Symposium on Methodologies for Intelligent Systems: ISMIS 2020
This book constitutes the proceedings of the 25th International Symposium on Foundations of Intelligent Systems, ISMIS 2020, held in Graz, Austria, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 35 full and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. Included is also ...
Added: October 4, 2020
, , et al., Advances in Systems Science and Applications 2018 Vol. 18 No. 4 P. 1-12
In this paper, we consider the problem of fine-tuning a discrete event simulator of distributed storage system by a neural network trained with reinforcement learning algorithms on real data. The simulator has a set of control parameters that affect its behaviour and can be tuned during the simulation. Variation of these parameters influences how realistic ...
Added: February 2, 2019
, , et al., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 2 С. 75-95
In this paper we consider the Shape Boltzmann Machine(SBM) and its multi-label version MSBM. We present an algorithm for training MSBM using only binary masks of objects and the seeds which approximately correspond to the locations of objects parts. ...
Added: September 30, 2015
Proceedings of the VI International conference Information Technology and Nanotechnology. Session Image Processing and Earth Remote Sensing (ITNT-IPERS)
Samara: CEUR Workshop Proceedings, 2020
This volume contains the papers presented at the session "Image Processing and Earth Remote Sensing" within the VI International Conference on Information Technology and Nanotechnology (ITNT-2020). The conference was held in Samara, Russia, during May 26-29, 2020 (itnt-conf.org). The conference is a forum for leading researchers from all over the world aimed to discuss the ...
Added: October 1, 2020
, , et al., Proceedings of Machine Learning Research 2020 P. 1-9
We propose a novel method for gradient-based optimization of black-box simulators using differentiable local surrogate models. In fields such as physics and engineering, many processes are modeled with non-differentiable simulators with intractable likelihoods. Optimization of these forward models is particularly challenging, especially when the simulator is stochastic. To address such cases, we introduce the use ...
Added: October 31, 2019
, , PeerJ Computer Science 2020 Vol. 6 No. e317 P. 1-22
Autonomous driving highly depends on depth information for safe driving. Recently, major improvements have been taken towards improving both supervised and self-supervised methods for depth reconstruction. However, most of the current approaches focus on single frame depth estimation, where quality limit is hard to beat due to limitations of supervised learning of deep neural networks ...
Added: October 27, 2020
, , , Известия ЮФУ. Технические науки 2012 № 6 С. 144-148
This article is devoted to the method of initial image processing to use in stereovision systems. It is based on a modification of video stabilization approach . The method considers image rectification process as a sequence of transformations. Each transformation is found as a solution of optimization problem. The article describes mathematical model that fits ...
Added: October 16, 2017
Added: October 21, 2019
, , , Scientific Reports 2020 Vol. 10 P. 19134
Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy considerations about B- to Z-DNA transition using sequence information. Z-DNA CHiP-seq experiment results showed little overlap with Z-Hunt predictions implying that sequence information only is not ...
Added: December 11, 2020
Workshop on Compact Deep Neural Network Representation with Industrial Applications, Thirty-second Conference on Neural Information Processing Systems
Montréal: [б.и.], 2018
This workshop aims to bring together researchers, educators, practitioners who are interested in techniques as well as applications of making compact and efficient neural network representations. One main theme of the workshop discussion is to build up consensus in this rapidly developed field, and in particular, to establish close connection between researchers in Machine Learning ...
Added: December 5, 2018
NY: Springer, 2013
Added: September 24, 2014
Providence: IEEE, 2012
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on ...
Added: October 1, 2014
, , , Programming and Computer Software 2017 Vol. 43 No. 4 P. 224-229
The paper considers a problem of multiple person tracking. We present the algorithm to automatic people tracking on surveillance videos recorded by static cameras. Proposed algorithm is an extension of approach based on tracking-by-detection of people heads and data association using Markov chain Monte Carlo (MCMC). Short track fragments (tracklets) are built by local tracking ...
Added: March 14, 2018
, , , Bayesian Group Sparsification of Long Short-Term Memory Networks / . 2018.
We propose a new Bayesian sparsification technique for gated recurrent architectures that encounters for its recurrent specifics and gated mechanism. Our method eliminates neurons from the model and makes gates constant, not only compressing the network, but also significantly accelerating a forward pass. On the discriminative tasks our method compresses LSTM extremely, so that only ...
Added: October 16, 2018
, , , Journal of Physics: Conference Series 2021 Vol. 1740 Article 012031
Demographic and population structure inference is one of the most important problems in genomics. Population parameters such as effective population sizes, population split times and migration rates are of high interest both themselves and for many applications, e.g. for genome-wide association studies. Hidden Markov Model (HMM) based methods, such as PSMC, MSMC, coalHMM etc., proved ...
Added: May 17, 2021
, Real-time Streaming Wave-U-Net with Temporal Convolutions for Multichannel Speech Enhancement / Cornell University. Series Computer Science "arxiv.org". 2021.
In this paper we describe our work that we have done to participate in Task1 of ConferencingSpeech2021 challenge. This task set a goal to develop the solution for multi-channel speech enhancement in a real-time manner. We propose a novel system for streaming speech enhancement. We employ Wave-U-Net architecture with temporal convolutions in encoder and decoder. ...
Added: September 26, 2021