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Bosch Deep Learning Hardware Benchmark
The widespread use of Deep Learning (DL) applications in science and ind...
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Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Post-hoc calibration is a common approach for providing high-quality con...
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On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration
Uncertainty estimates help to identify ambiguous, novel, or anomalous in...
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Robust Anomaly Detection in Images using Adversarial Autoencoders
Reliably detecting anomalies in a given set of images is a task of high ...
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Data-driven Summarization of Scientific Articles
Data-driven approaches to sequence-to-sequence modelling have been succe...
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Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks
Deep convolutional neural networks (CNNs) have shown great potential for...
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Deep counter networks for asynchronous event-based processing
Despite their advantages in terms of computational resources, latency, a...
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Prediction of Manipulation Actions
Looking at a person's hands one often can tell what the person is going ...
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Training Deep Spiking Neural Networks using Backpropagation
Deep spiking neural networks (SNNs) hold great potential for improving t...
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Precise deep neural network computation on imprecise low-power analog hardware
There is an urgent need for compact, fast, and power-efficient hardware ...
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Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest
Colorectal adenocarcinoma originating in intestinal glandular structures...
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Spiking Analog VLSI Neuron Assemblies as Constraint Satisfaction Problem Solvers
Solving constraint satisfaction problems (CSPs) is a notoriously expensi...
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