Zobrazeno 1 - 10
of 6 891
pro vyhledávání: '"ZHANG Yingying"'
Autor:
Wang, Xiaolong, Yu, Lei, Zhang, Yingying, Lao, Jiangwei, Ru, Lixiang, Zhong, Liheng, Chen, Jingdong, Zhang, Yu, Yang, Ming
Feature matching between image pairs is a fundamental problem in computer vision that drives many applications, such as SLAM. Recently, semi-dense matching approaches have achieved substantial performance enhancements and established a widely-accepte
Externí odkaz:
http://arxiv.org/abs/2411.06700
Autor:
Chen, Feiyi, Zhang, Yingying, Fan, Lunting, Liang, Yuxuan, Pang, Guansong, Wen, Qingsong, Deng, Shuiguang
Slow task detection is a critical problem in cloud operation and maintenance since it is highly related to user experience and can bring substantial liquidated damages. Most anomaly detection methods detect it from a single-task aspect. However, cons
Externí odkaz:
http://arxiv.org/abs/2408.04236
Autor:
Zhang, Yingying, Guo, Xin, Lao, Jiangwei, Yu, Lei, Ru, Lixiang, Wang, Jian, Ye, Guo, He, Huimei, Chen, Jingdong, Yang, Ming
Large-scale self-supervised pre-training has paved the way for one foundation model to handle many different vision tasks. Most pre-training methodologies train a single model of a certain size at one time. Nevertheless, various computation or storag
Externí odkaz:
http://arxiv.org/abs/2408.01031
Autor:
Zheng, Junling, Zhang, Yingying
Publikováno v:
Arch. Math. (Basel),2024
There is a well-known class of algebras called Igusa-Todorov algebras which were introduced in relation to finitistic dimension conjecture. As a generalization of Igusa-Todorov algebras, the new notion of $(m,n)$-Igusa-Todorov algebras provides a wid
Externí odkaz:
http://arxiv.org/abs/2406.16011
Autor:
Zhang, Yingying, Shi, Chuangji, Guo, Xin, Lao, Jiangwei, Wang, Jian, Wang, Jiaotuan, Chen, Jingdong
The design of the query is crucial for the performance of DETR and its variants. Each query consists of two components: a content part and a positional one. Traditionally, the content query is initialized with a zero or learnable embedding, lacking e
Externí odkaz:
http://arxiv.org/abs/2405.03318
Autor:
Aoki, Toshitaka, Zhang, Yingying
For Brauer graph algebras, tilting mutation is compatible with flip of Brauer graphs. The aim of this paper is to generalize this result to the class of Brauer configuration algebras introduced by Green and Schroll recently. More precisely, under a c
Externí odkaz:
http://arxiv.org/abs/2403.14134
Multi-span answer extraction, also known as the task of multi-span question answering (MSQA), is critical for real-world applications, as it requires extracting multiple pieces of information from a text to answer complex questions. Despite the activ
Externí odkaz:
http://arxiv.org/abs/2402.09923
Autor:
Chen, Peng, Zhang, Yingying, Cheng, Yunyao, Shu, Yang, Wang, Yihang, Wen, Qingsong, Yang, Bin, Guo, Chenjuan
Transformers for time series forecasting mainly model time series from limited or fixed scales, making it challenging to capture different characteristics spanning various scales. We propose Pathformer, a multi-scale Transformer with adaptive pathway
Externí odkaz:
http://arxiv.org/abs/2402.05956
Autor:
Liu, Zichuan, Zhang, Yingying, Wang, Tianchun, Wang, Zefan, Luo, Dongsheng, Du, Mengnan, Wu, Min, Wang, Yi, Chen, Chunlin, Fan, Lunting, Wen, Qingsong
Explaining multivariate time series is a compound challenge, as it requires identifying important locations in the time series and matching complex temporal patterns. Although previous saliency-based methods addressed the challenges, their perturbati
Externí odkaz:
http://arxiv.org/abs/2401.08552