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10/11/2022
RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks
Neural Architecture Search (NAS) algorithms aim at finding efficient Dee...
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09/26/2022
Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile
Most of today's computer vision pipelines are built around deep neural n...
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06/21/2022
Enabling Capsule Networks at the Edge through Approximate Softmax and Squash Operations
Complex Deep Neural Networks such as Capsule Networks (CapsNets) exhibit...
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12/21/2020
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life...
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08/19/2020
NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks
Deep Neural Networks (DNNs) have made significant improvements to reach ...
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04/15/2020
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks
Capsule Networks (CapsNets), recently proposed by the Google Brain team,...
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05/24/2019
