33 results on '"Daniel Neil"'
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2. DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction.
3. Lip Reading Deep Network Exploiting Multi-Modal Spiking Visual and Auditory Sensors.
4. Attention-driven Multi-sensor Selection.
5. Multi-channel Attention for End-to-End Speech Recognition.
6. DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator.
7. A curriculum learning method for improved noise robustness in automatic speech recognition.
8. Delta Networks for Optimized Recurrent Network Computation.
9. DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction.
10. Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences.
11. Combined frame- and event-based detection and tracking.
12. Event-driven deep neural network hardware system for sensor fusion.
13. Effective sensor fusion with event-based sensors and deep network architectures.
14. Temporal sequence recognition in a self-organizing recurrent network.
15. Steering a predator robot using a mixed frame/event-driven convolutional neural network.
16. Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks.
17. Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design.
18. Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing.
19. Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker.
20. PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing.
21. Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs.
22. ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation.
23. Sensor Transformation Attention Networks.
24. DDD17: End-To-End DAVIS Driving Dataset.
25. Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator.
26. Live demonstration: Event-driven real-time spoken digit recognition system.
27. A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition.
28. Precise deep neural network computation on imprecise low-power analog hardware.
29. Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences.
30. Delta Networks for Optimized Recurrent Network Computation.
31. Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Network.
32. Live demonstration: Event-driven deep neural network hardware system for sensor fusion.
33. Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker.
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