Zobrazeno 1 - 10
of 233
pro vyhledávání: '"Zhao, Mingjun"'
Autor:
Fathi, Faraneh, Mazdeyasna, Siavash, Singh, Dara, Huang, Chong, Mohtasebi, Mehrana, Liu, Xuhui, Haratbar, Samaneh Rabienia, Zhao, Mingjun, Chen, Li, Ulku, Arin Can, Mos, Paul, Bruschini, Claudio, Charbon, Edoardo, Chen, Lei, Yu, Guoqiang
To address many of the deficiencies in optical neuroimaging technologies such as poor spatial resolution, time-consuming reconstruction, low penetration depth, and contact-based measurement, a novel, noncontact, time-resolved laser speckle contrast i
Externí odkaz:
http://arxiv.org/abs/2309.13527
Autor:
Yu, Yakun, Zhao, Mingjun, Qi, Shi-ang, Sun, Feiran, Wang, Baoxun, Guo, Weidong, Wang, Xiaoli, Yang, Lei, Niu, Di
Multimodal Sentiment Analysis leverages multimodal signals to detect the sentiment of a speaker. Previous approaches concentrate on performing multimodal fusion and representation learning based on general knowledge obtained from pretrained models, w
Externí odkaz:
http://arxiv.org/abs/2306.15796
Text clustering, as one of the most fundamental challenges in unsupervised learning, aims at grouping semantically similar text segments without relying on human annotations. With the rapid development of deep learning, deep clustering has achieved s
Externí odkaz:
http://arxiv.org/abs/2304.11061
Despite the success of deep learning in video understanding tasks, processing every frame in a video is computationally expensive and often unnecessary in real-time applications. Frame selection aims to extract the most informative and representative
Externí odkaz:
http://arxiv.org/abs/2304.10316
Automated augmentation is an emerging and effective technique to search for data augmentation policies to improve generalizability of deep neural network training. Most existing work focuses on constructing a unified policy applicable to all data sam
Externí odkaz:
http://arxiv.org/abs/2304.10310
Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user instructions.Although the synthesis performance is fascinating, one sig
Externí odkaz:
http://arxiv.org/abs/2303.17870
Autor:
Li, Chenglin, Zhao, Mingjun, Zhang, Huanming, Yu, Chenyun, Cheng, Lei, Shu, Guoqiang, Kong, Beibei, Niu, Di
Cross-domain recommendation can help alleviate the data sparsity issue in traditional sequential recommender systems. In this paper, we propose the RecGURU algorithm framework to generate a Generalized User Representation (GUR) incorporating user inf
Externí odkaz:
http://arxiv.org/abs/2111.10093
Autor:
Guo, Weidong, Zhao, Mingjun, Zhang, Lusheng, Niu, Di, Luo, Jinwen, Liu, Zhenhua, Li, Zhenyang, Tang, Jianbo
Language model pre-training based on large corpora has achieved tremendous success in terms of constructing enriched contextual representations and has led to significant performance gains on a diverse range of Natural Language Understanding (NLU) ta
Externí odkaz:
http://arxiv.org/abs/2108.00801
Publikováno v:
In Ceramics International 1 May 2024 50(9) Part B:15677-15689
Translation Quality Estimation is critical to reducing post-editing efforts in machine translation and to cross-lingual corpus cleaning. As a research problem, quality estimation (QE) aims to directly estimate the quality of translation in a given pa
Externí odkaz:
http://arxiv.org/abs/2105.14878