Tianhong Dai
Cited by
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LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning
Y Du, L Han, M Fang, J Liu, T Dai, D Tao
Advances in Neural Information Processing Systems, 4403-4414, 2019
Image Synthesis with a Convolutional Capsule Generative Adversarial Network
C Bass, T Dai, B Billot, K Arulkumaran, A Creswell, C Clopath, V De Paola, ...
International Conference on Medical Imaging with Deep Learning, 39-62, 2019
Deep Reinforcement Learning for Subpixel Neural Tracking
T Dai, M Dubois, K Arulkumaran, J Campbell, C Bass, B Billot, F Uslu, ...
International Conference on Medical Imaging with Deep Learning, 130-150, 2019
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
T Dai, K Arulkumaran, T Gerbert, S Tukra, F Behbahani, AA Bharath
arXiv preprint arXiv:1912.08324, 2019
Coupled Network for Robust Pedestrian Detection with Gated Multi-layer Feature Extraction and Deformable Occlusion Handling
T Liu, W Luo, L Ma, JJ Huang, T Stathaki, T Dai
IEEE Transactions on Image Processing, 2020
Gated Multi-Layer Convolutional Feature Extraction Network for Robust Pedestrian Detection
T Liu, JJ Huang, T Dai, G Ren, T Stathaki
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2020
Episodic Self-Imitation Learning with Hindsight
T Dai, H Liu, AA Bharath
Electronics 9 (10), 1742, 2020
Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network
G Ren, T Dai, P Barmpoutis, T Stathaki
arXiv preprint arXiv:2004.14552, 2020
A Maximum Entropy Deep Reinforcement Learning Neural Tracker
S Balaram, K Arulkumaran, T Dai, AA Bharath
International Workshop on Machine Learning in Medical Imaging, 400-408, 2019
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