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Sequential Image Classification

8 papers with code · Computer Vision

Sequential image classification is the task of classifying a sequence of images.

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Latest papers with code

R-Transformer: Recurrent Neural Network Enhanced Transformer

12 Jul 2019DSE-MSU/R-transformer

Recurrent Neural Networks have long been the dominating choice for sequence modeling.

LANGUAGE MODELLING MUSIC MODELING SEQUENTIAL IMAGE CLASSIFICATION

144
12 Jul 2019

Trellis Networks for Sequence Modeling

ICLR 2019 locuslab/trellisnet

On the other hand, we show that truncated recurrent networks are equivalent to trellis networks with special sparsity structure in their weight matrices.

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION

370
15 Oct 2018

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

4 Mar 2018locuslab/TCN

Our results indicate that a simple convolutional architecture outperforms canonical recurrent networks such as LSTMs across a diverse range of tasks and datasets, while demonstrating longer effective memory.

LANGUAGE MODELLING MACHINE TRANSLATION MUSIC MODELING SEQUENTIAL IMAGE CLASSIFICATION

1,947
04 Mar 2018

Dilated Recurrent Neural Networks

NeurIPS 2017 code-terminator/DilatedRNN

To provide a theory-based quantification of the architecture's advantages, we introduce a memory capacity measure, the mean recurrent length, which is more suitable for RNNs with long skip connections than existing measures.

SEQUENTIAL IMAGE CLASSIFICATION

316
05 Oct 2017

Full-Capacity Unitary Recurrent Neural Networks

NeurIPS 2016 stwisdom/urnn

To address this question, we propose full-capacity uRNNs that optimize their recurrence matrix over all unitary matrices, leading to significantly improved performance over uRNNs that use a restricted-capacity recurrence matrix.

SEQUENTIAL IMAGE CLASSIFICATION

50
31 Oct 2016

Recurrent Batch Normalization

30 Mar 2016cooijmanstim/recurrent-batch-normalization

We propose a reparameterization of LSTM that brings the benefits of batch normalization to recurrent neural networks.

LANGUAGE MODELLING QUESTION ANSWERING READING COMPREHENSION SEQUENTIAL IMAGE CLASSIFICATION

59
30 Mar 2016

Unitary Evolution Recurrent Neural Networks

20 Nov 2015Avmb/lowrank-gru

When the eigenvalues of the hidden to hidden weight matrix deviate from absolute value 1, optimization becomes difficult due to the well studied issue of vanishing and exploding gradients, especially when trying to learn long-term dependencies.

SEQUENTIAL IMAGE CLASSIFICATION

31
20 Nov 2015

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

3 Apr 2015trevor-richardson/rnn_zoo

Learning long term dependencies in recurrent networks is difficult due to vanishing and exploding gradients.

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION SPEECH RECOGNITION

3
03 Apr 2015