Zobrazeno 1 - 10
of 18 078
pro vyhledávání: '"Xu,Min"'
It is widely agreed that open-vocabulary-based approaches outperform classical closed-set training solutions for recognizing unseen objects in images for semantic segmentation. Existing open-vocabulary approaches leverage vision-language models, such
Externí odkaz:
http://arxiv.org/abs/2412.00364
Cryo-Electron Tomography (Cryo-ET) enables detailed 3D visualization of cellular structures in near-native states but suffers from low signal-to-noise ratio due to imaging constraints. Traditional denoising methods and supervised learning approaches
Externí odkaz:
http://arxiv.org/abs/2411.15248
With the growing application of transformer in computer vision, hybrid architecture that combine convolutional neural networks (CNNs) and transformers demonstrates competitive ability in medical image segmentation. However, direct fusion of features
Externí odkaz:
http://arxiv.org/abs/2411.10881
Recent attention-based volumetric segmentation (VS) methods have achieved remarkable performance in the medical domain which focuses on modeling long-range dependencies. However, for voxel-wise prediction tasks, discriminative local features are key
Externí odkaz:
http://arxiv.org/abs/2410.01003
High-resolution images are preferable in medical imaging domain as they significantly improve the diagnostic capability of the underlying method. In particular, high resolution helps substantially in improving automatic image segmentation. However, m
Externí odkaz:
http://arxiv.org/abs/2410.00986
Generalized Category Discovery (GCD) aims to classify inputs into both known and novel categories, a task crucial for open-world scientific discoveries. However, current GCD methods are limited to unimodal data, overlooking the inherently multimodal
Externí odkaz:
http://arxiv.org/abs/2409.11624
We investigate linear network coding in the context of robust function computation, where a sink node is tasked with computing a target function of messages generated at multiple source nodes. In a previous work, a new distance measure was introduced
Externí odkaz:
http://arxiv.org/abs/2409.10854
Autor:
Wu, Niannian, Yang, Zongyu, Li, Rongpeng, Wei, Ning, Chen, Yihang, Dong, Qianyun, Li, Jiyuan, Zheng, Guohui, Gong, Xinwen, Gao, Feng, Li, Bo, Xu, Min, Zhao, Zhifeng, Zhong, Wulyu
The drive to control tokamaks, a prominent technology in nuclear fusion, is essential due to its potential to provide a virtually unlimited source of clean energy. Reinforcement learning (RL) promises improved flexibility to manage the intricate and
Externí odkaz:
http://arxiv.org/abs/2409.09238
Cross-domain recommendation (CDR) aims to improve recommendation accuracy in sparse domains by transferring knowledge from data-rich domains. However, existing CDR methods often assume the availability of user-item interaction data across domains, ov
Externí odkaz:
http://arxiv.org/abs/2409.03294
Large language models (LLMs) and retrieval-augmented generation (RAG) techniques have revolutionized traditional information access, enabling AI agent to search and summarize information on behalf of users during dynamic dialogues. Despite their pote
Externí odkaz:
http://arxiv.org/abs/2409.00636