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Sequential Image Classification

13 papers with code · Computer Vision

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

( Image credit: TensorFlow-101 )

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Recurrent Highway Networks with Grouped Auxiliary Memory

IEEE Access 2019 WilliamRo/gam_rhn

In this paper, we address these issues by proposing a novel RNN architecture based on RHN, namely the Recurrent Highway Network with Grouped Auxiliary Memory (GAM-RHN).

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION STOCK TREND PREDICTION

6
13 Dec 2019

Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

ICLR 2020 0zgur0/STAR_Network

We propose a new stackable recurrent cell (STAR) for recurrent neural networks (RNNs) that has significantly less parameters than widely used LSTM and GRU while being more robust against vanishing or exploding gradients.

#2 best model for Sequential Image Classification on Sequential MNIST (Unpermuted Accuracy metric)

ACTION RECOGNITION IN VIDEOS LANGUAGE MODELLING MUSIC MODELING SEQUENTIAL IMAGE CLASSIFICATION

8
25 Nov 2019

Deep Independently Recurrent Neural Network (IndRNN)

11 Oct 2019Sunnydreamrain/IndRNN_pytorch

Experimental results have shown that the proposed IndRNN is able to process very long sequences (over 5000 time steps), can be used to construct very deep networks (the 21 layers residual IndRNN and deep densely connected IndRNN used in the experiment for example).

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION SKELETON BASED ACTION RECOGNITION

71
11 Oct 2019

Learning to Remember More with Less Memorization

ICLR 2019 thaihungle/UW-DNC

Memory-augmented neural networks consisting of a neural controller and an external memory have shown potentials in long-term sequential learning.

SENTIMENT ANALYSIS SEQUENTIAL IMAGE CLASSIFICATION TEXT CLASSIFICATION

14
05 Jan 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

399
15 Oct 2018

Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

CVPR 2018 TobiasLee/Text-Classification

Experimental results have shown that the proposed IndRNN is able to process very long sequences (over 5000 time steps), can be used to construct very deep networks (21 layers used in the experiment) and still be trained robustly.

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION SKELETON BASED ACTION RECOGNITION

627
13 Mar 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

2,256
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

331
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

53
31 Oct 2016