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Found 9 papers, 2 papers with code
Sharpening Your Density Fields: Spiking Neuron Aided Fast Geometry Learning
Neural Radiance Fields (NeRF) have achieved remarkable progress in neural rendering.
Robust SG-NeRF: Robust Scene Graph Aided Neural Surface Reconstruction
We also devise a scene graph updating strategy to provide more accurate information throughout the training process.
Receiver-Centric Generative Semantic Communications
To solve this problem, this paper presents a receiver-centric generative semantic communication system, where each transmission is initialized by the receiver.
Finding Defective Elements in Intelligent Reflecting Surface via Over-the-Air Measurements
Based on this observation, we propose a bisection based method to localize all the defective IRS elements.
When Spiking neural networks meet temporal attention image decoding and adaptive spiking neuron
Furthermore, our ALIF neuron model achieves remarkable classification accuracy on MNIST (99. 78\%) and CIFAR-10 (93. 89\%) datasets, demonstrating the effectiveness of learning adaptive thresholds for spiking neurons.
Combating Multi-path Interference to Improve Chirp-based Underwater Acoustic Communication
Linear chirp-based underwater acoustic communication has been widely used due to its reliability and long-range transmission capability.
Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks
Experiments on CIFAR10/100 and ImageNet datasets demonstrate that GAC achieves state-of-the-art accuracy with remarkable efficiency.
Ranked #110 on
Image Classification
on CIFAR-10
Reducing Channel Estimation and Feedback Overhead in IRS-Aided Downlink System: A Quantize-then-Estimate Approach
Recently, [1] revealed a strong correlation in different users' cascaded channels stemming from their common BS-IRS channel component, and leveraged such a correlation to significantly reduce the pilot transmission overhead in IRS-aided uplink communication.
Quick and Reliable LoRa Physical-layer Data Aggregation through Multi-Packet Reception
Trace-driven simulation results show that the symbol demodulation algorithm outperforms the state-of-the-art MPR decoder by 5. 3$\times$ in terms of physical-layer throughput, and the soft decoder is more robust to unavoidable adverse phase misalignment and estimation error in practice.
