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Sequential Image Classification

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

( Image credit: TensorFlow-101 )

Papers

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Showing 1–44 of 44 papers

TitleStatusHype
UnICORNN: A recurrent model for learning very long time dependenciesCode1
Learning Long-Term Dependencies in Irregularly-Sampled Time SeriesCode1
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over ModulesCode1
Learning to Remember More with Less MemorizationCode1
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural NetworksCode1
Lipschitz Recurrent Neural NetworksCode1
CKConv: Continuous Kernel Convolution For Sequential DataCode1
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependenciesCode1
Traveling Waves Encode the Recent Past and Enhance Sequence LearningCode1
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
SMPConv: Self-moving Point Representations for Continuous ConvolutionCode1
Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place RecognitionCode1
Efficiently Modeling Long Sequences with Structured State SpacesCode1
Efficient recurrent architectures through activity sparsity and sparse back-propagation through timeCode1
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel SizesCode1
Sequence Modeling with Multiresolution Convolutional MemoryCode1
Resurrecting Recurrent Neural Networks for Long SequencesCode1
HiPPO: Recurrent Memory with Optimal Polynomial ProjectionsCode1
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence ModelingCode1
Parallelizing Legendre Memory Unit TrainingCode1
Long Expressive Memory for Sequence ModelingCode1
VCI-LSTM: Vector Choquet Integral-based Long Short-Term Memory—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Cortical microcircuits as gated-recurrent neural networks—0
Image Classification using Sequence of Pixels—0
Learning Long Sequences in Spiking Neural Networks—0
Minion Gated Recurrent Unit for Continual Learning—0
Long short-term memory and learning-to-learn in networks of spiking neuronsCode0
AntisymmetricRNN: A Dynamical System View on Recurrent Neural NetworksCode0
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Recurrent Batch NormalizationCode0
Recurrent Highway Networks with Grouped Auxiliary MemoryCode0
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural NetworksCode0
Gating Revisited: Deep Multi-layer RNNs That Can Be TrainedCode0
R-Transformer: Recurrent Neural Network Enhanced TransformerCode0
Full-Capacity Unitary Recurrent Neural NetworksCode0
Dilated Recurrent Neural NetworksCode0
Delayed Memory Unit: Modelling Temporal Dependency Through Delay GateCode0
Deep Independently Recurrent Neural Network (IndRNN)Code0
Trellis Networks for Sequence ModelingCode0
A Simple Way to Initialize Recurrent Networks of Rectified Linear UnitsCode0
Unitary Evolution Recurrent Neural NetworksCode0
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNNCode0
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