Self-Supervised Discovering of Interpretable Features for Reinforcement Learning
Deep reinforcement learning (RL) has recently led to many breakthroughs on a range of complex control tasks. However, the agent’s decision-making process is generally not transparent. The lack of…
Prior Guided Feature Enrichment Network for Few-Shot Segmentation
State-of-the-art semantic segmentation methods require sufficient labeled data to achieve good results and hardly work on unseen classes without fine-tuning. Few-shot segmentation is thus proposed …
Closed-Loop Method Based on Faraday Effect in Resonant Fiber Optic Gyro Emplo…
The closed-loop method based on the Faraday effect is realized with a low coherence-noise resonator in resonance fiber optic gyro (RFOG). The resonator based on spun-fiber (SF) is designed and fabr…
Matching Returning Donors to Projects on Philanthropic Crowdfunding Platforms
We propose an approach to match returning donors to fundraising campaigns on philanthropic crowdfunding platforms. It is based on a structural econometric model of utility-maximizing donors who can…
Numerical Investigation of All-Optical Manipulation for Polarization-Multiple…
Temporal cavity solitons (CSs) are pulses that can maintain their shape and circulate indefinitely in a resonant cavity under coherent driving. The approach for writing, erasing, and moving of CSs …
Symmetry Breaking and Resonances Hybridization in Vertical Split Ring Resonat…
The resonances with narrow linewidths generated in metamaterials are valuable for numerous applications ranging from bio-sensing to narrow-band filter. And breaking structural symmetry of metamater…
Spectrum Intelligent Radio : Technology, Development, and Future Trends
The advent of Industry 4.0 with massive connectivity places significant strains on the current spectrum resources, and challenges the industry and regulators to respond promptly with new disruptive…
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