An Efficient Recurrent Unit (ERU) extends LSTM-based language models by replacing linear transforms for processing the input vector with the EESP unit inside the LSTM cell.
Source: ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
Visual Grounding | 1 | 12.50% |
General Classification | 1 | 12.50% |
Image Classification | 1 | 12.50% |
Language Modelling | 1 | 12.50% |
Object Detection | 1 | 12.50% |
Real-Time Object Detection | 1 | 12.50% |
Real-Time Semantic Segmentation | 1 | 12.50% |
Semantic Segmentation | 1 | 12.50% |
Component | Type |
|
---|---|---|
Dropout
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Regularization | |
EESP
|
Image Model Blocks | |
LSTM
|
Recurrent Neural Networks |