Speeding up convolutional neural networks with low rank expansions

Speeding up convolutional neural networks with low rank expansions

Show other versions (1)

The focus of this paper is speeding up the application of convolutional neural networks. While delivering impressive results across a range of computer vision and machine learning tasks, these networks are computationally demanding, limiting their deployability. Convolutional layers generally consum...

Deskribapen osoa

Xehetasun bibliografikoak
Egile Nagusiak:	Jaderberg, M, Vedaldi, A, Zisserman, A
Formatua:	Conference item
Argitaratua:	BMVA Press 2014

Antzeko izenburuak

Speeding up convolutional neural networks with low rank expansions
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Reading text in the wild with convolutional neural networks
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Reading text in the wild with convolutional neural networks
nork: Jaderberg, M, et al.
Argitaratua: (2015)

Synthetic data and artificial neural networks for natural scene text recognition
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Synthetic data and artificial neural networks for natural scene text recognition
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Deep features for text spotting
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Speeding-up convolutional neural networks: A survey
nork: V. Lebedev, et al.
Argitaratua: (2018-12-01)

Deep structured output learning for unconstrained text recognition
nork: Jaderberg, M, et al.
Argitaratua: (2014)

Deep structured output learning for unconstrained text recognition
nork: Jaderberg, M, et al.
Argitaratua: (2015)

Deep inside convolutional networks: visualising image classification models and saliency maps
nork: Simonyan, K, et al.
Argitaratua: (2014)

Simultaneous object detection and ranking with weak supervision
nork: Blaschko, MB, et al.
Argitaratua: (2011)

Remarks on Speeding up the Digital Camera Identification using Convolutional Neural Networks
nork: Jaroslaw Bernacki, et al.
Argitaratua: (2023-11-01)

Visualizing deep convolutional neural networks using natural pre-images
nork: Mahendran, A, et al.
Argitaratua: (2016)

Stable Low-Rank CP Decomposition for Compression of Convolutional Neural Networks Based on Sensitivity
nork: Chenbin Yang, et al.
Argitaratua: (2024-02-01)

Automatically discovering and learning new visual categories with ranking statistics
nork: Han, K, et al.
Argitaratua: (2020)

Gather-excite: Exploiting feature context in convolutional neural networks
nork: Hu, J, et al.
Argitaratua: (2018)

Colorectal cancer detection based on convolutional neural networks (CNN) and ranking algorithm
nork: A. Karthikeyan, et al.
Argitaratua: (2024-02-01)

Convolutional Neural Network Compression via Dynamic Parameter Rank Pruning
nork: Manish Sharma, et al.
Argitaratua: (2025-01-01)

Return of the devil in the details: delving deep into convolutional nets
nork: Chatfield, K, et al.
Argitaratua: (2014)

Return of the devil in the details: delving deep into convolutional nets
nork: Chatfield, K, et al.
Argitaratua: (2014)

Using Low-Rank Approximations to Speed Up Kernel Logistic Regression Algorithm
nork: Dajiang Lei, et al.
Argitaratua: (2019-01-01)

Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem
nork: Benjamin Flück, et al.
Argitaratua: (2022-06-01)

Data‐driven flood emulation: Speeding up urban flood predictions by deep convolutional neural networks
nork: Zifeng Guo, et al.
Argitaratua: (2021-03-01)

A Training Method for Low Rank Convolutional Neural Networks Based on Alternating Tensor Compose-Decompose Method
nork: Sukho Lee, et al.
Argitaratua: (2021-01-01)

Deep convolutional neural networks for efficient pose estimation in gesture videos
nork: Pfister, T, et al.
Argitaratua: (2015)

Modeling urban expansion by integrating a convolutional neural network and a recurrent neural network
nork: Xinhao Pan, et al.
Argitaratua: (2022-08-01)

FOV Expansion of Bioinspired Multiband Polarimetric Imagers With Convolutional Neural Networks
nork: Yongqiang Zhao, et al.
Argitaratua: (2018-01-01)

On Generalization Bounds for Neural Networks with Low Rank Layers
nork: Pinto, Andrea, et al.
Argitaratua: (2024)

The impact of sparsity in low-rank recurrent neural networks.
nork: Elizabeth Herbert, et al.
Argitaratua: (2022-08-01)

Bayesian Optimization-Based Global Optimal Rank Selection for Compression of Convolutional Neural Networks
nork: Taehyeon Kim, et al.
Argitaratua: (2020-01-01)

Fully Convolutional Neural Network for Vehicle Speed and Emergency-Brake Prediction
nork: Razvan Itu, et al.
Argitaratua: (2023-12-01)

Convolutional neural network in rice disease recognition: accuracy, speed and lightweight
nork: Hongwei Ning, et al.
Argitaratua: (2023-11-01)

Traffic flow speed prediction on transportation graph with convolutional neural networks
nork: Nikolay G. Prokoptsev, et al.
Argitaratua: (2018-06-01)

Low power convolutional neural network (CNN)
nork: Lim, Wu Cong
Argitaratua: (2019)

Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction
nork: Ziqi Chen, et al.
Argitaratua: (2021-05-01)

Cerebral Micro-Bleed Detection Based on the Convolution Neural Network With Rank Based Average Pooling
nork: Shuihua Wang, et al.
Argitaratua: (2017-01-01)

Re-Training of Convolutional Neural Networks for Glottis Segmentation in Endoscopic High-Speed Videos
nork: Michael Döllinger, et al.
Argitaratua: (2022-09-01)

Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie
nork: Kaiwei Liang, et al.
Argitaratua: (2018-01-01)

Depthwise Separable Convolution Neural Network for High-Speed SAR Ship Detection
nork: Tianwen Zhang, et al.
Argitaratua: (2019-10-01)

A Convolutional Neural Network for Gender Recognition Optimizing the Accuracy/Speed Tradeoff
nork: Antonio Greco, et al.
Argitaratua: (2020-01-01)