Zobrazeno 1 - 10
of 21 146
pro vyhledávání: '"Xiwen"'
Traffic accident prediction is crucial for enhancing road safety and mitigating congestion, and recent Graph Neural Networks (GNNs) have shown promise in modeling the inherent graph-based traffic data. However, existing GNN- based approaches often ov
Externí odkaz:
http://arxiv.org/abs/2412.02839
Autor:
Wang, Hao, Zhu, Wenhui, Dong, Xuanzhao, Chen, Yanxi, Li, Xin, Qiu, Peijie, Chen, Xiwen, Vasa, Vamsi Krishna, Xiong, Yujian, Dumitrascu, Oana M., Razi, Abolfazl, Wang, Yalin
In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training mul
Externí odkaz:
http://arxiv.org/abs/2412.02825
Catastrophic forgetting is a significant challenge in online continual learning (OCL), especially for non-stationary data streams that do not have well-defined task boundaries. This challenge is exacerbated by the memory constraints and privacy conce
Externí odkaz:
http://arxiv.org/abs/2411.05663
Autor:
Yi, Rongjie, Li, Xiang, Xie, Weikai, Lu, Zhenyan, Wang, Chenghua, Zhou, Ao, Wang, Shangguang, Zhang, Xiwen, Xu, Mengwei
The interest in developing small language models (SLM) for on-device deployment is fast growing. However, the existing SLM design hardly considers the device hardware characteristics. Instead, this work presents a simple yet effective principle for S
Externí odkaz:
http://arxiv.org/abs/2411.05046
Enhancing Graph Neural Networks in Large-scale Traffic Incident Analysis with Concurrency Hypothesis
Despite recent progress in reducing road fatalities, the persistently high rate of traffic-related deaths highlights the necessity for improved safety interventions. Leveraging large-scale graph-based nationwide road network data across 49 states in
Externí odkaz:
http://arxiv.org/abs/2411.02542
Autor:
Li, Xiwen, Mohammed, Rehman, Mangin, Tristalee, Saha, Surojit, Whitaker, Ross T, Kelly, Kerry E., Tasdizen, Tolga
Idling vehicle detection (IVD) can be helpful in monitoring and reducing unnecessary idling and can be integrated into real-time systems to address the resulting pollution and harmful products. The previous approach [13], a non-end-to-end model, requ
Externí odkaz:
http://arxiv.org/abs/2410.21170
Autor:
Li, Jiachen, Steinberg, Justin, Li, Xiwen, Choube, Akshat, Yao, Bingsheng, Wang, Dakuo, Mynatt, Elizabeth, Mishra, Varun
Researchers have long recognized the socio-technical gaps in personal tracking research, where machines can never fully model the complexity of human behavior, making it only able to produce basic rule-based outputs or "black-box" results that lack c
Externí odkaz:
http://arxiv.org/abs/2410.14879
With the rapid advances in diffusion models, generating decent images from text prompts is no longer challenging. The key to text-to-image generation is how to optimize the results of a text-to-image generation model so that they can be better aligne
Externí odkaz:
http://arxiv.org/abs/2410.10257
In recent years, significant progress has been made in the medical image analysis domain using convolutional neural networks (CNNs). In particular, deep neural networks based on a U-shaped architecture (UNet) with skip connections have been adopted f
Externí odkaz:
http://arxiv.org/abs/2410.11578