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11/09/2022
Affordance detection with Dynamic-Tree Capsule Networks
Affordance detection from visual input is a fundamental step in autonomo...
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08/01/2022
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization
Training deep neural networks is a very demanding task, especially chall...
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02/14/2022
Continual Learning from Demonstration of Robotic Skills
Methods for teaching motion skills to robots focus on training for a sin...
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01/26/2022
Momentum Capsule Networks
Capsule networks are a class of neural networks that achieved promising ...
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05/31/2021
Greedy Layer Pruning: Decreasing Inference Time of Transformer Models
Fine-tuning transformer models after unsupervised pre-training reaches a...
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04/15/2021
Training Deep Capsule Networks with Residual Connections
Capsule networks are a type of neural network that have recently gained ...
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03/07/2021
Auto-tuning of Deep Neural Networks by Conflicting Layer Removal
Designing neural network architectures is a challenging task and knowing...
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02/23/2021
Arguments for the Unsuitability of Convolutional Neural Networks for Non–Local Tasks
Convolutional neural networks have established themselves over the past ...
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11/05/2020
Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks
Designing neural network architectures is a challenging task and knowing...
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01/29/2020
Evaluating the Progress of Deep Learning for Visual Relational Concepts
Convolutional Neural Networks (CNNs) have become the state of the art me...
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05/21/2019
Limitations of routing-by-agreement based capsule networks
Classical neural networks add a bias term to the sum of all weighted inp...
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03/30/2019
Evaluating CNNs on the Gestalt Principle of Closure
Deep convolutional neural networks (CNNs) are widely known for their out...
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12/23/2018
Training Deep Capsule Networks
The capsules of Capsule Networks are collections of neurons that represe...
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12/06/2017
Guided Labeling using Convolutional Neural Networks
Over the last couple of years, deep learning and especially convolutiona...
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08/25/2017
Evaluation of Deep Learning on an Abstract Image Classification Dataset
Convolutional Neural Networks have become state of the art methods for i...
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07/28/2016
25 years of CNNs: Can we compare to human abstraction capabilities?
We try to determine the progress made by convolutional neural networks o...
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06/17/2016
Learning Abstract Classes using Deep Learning
Humans are generally good at learning abstract concepts about objects an...
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04/06/2013
