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Cuixia Li, Shanshan Yang, Li Shi, Yue Liu and Yinghao Li
Existing end-to-end cloud registration methods are often inefficient and susceptible to noise. We propose an end-to-end point cloud registration network model, Point Transformer for Registration Network (PTRNet), that considers local and global features ...
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Bhawna Mewara, Gunjan Sahni, Soniya Lalwani and Rajesh Kumar
Protein?protein interactions (PPIs) are involved in an extensive variety of biological procedures, including cell-to-cell interactions, and metabolic and developmental control. PPIs are becoming one of the most important aims of system biology. PPIs act ...
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Song Yuan, Zexin Lu, Qiyuan Li and Jinguang Gu
Due to inter-modal effects hidden in multi-modalities and the impact of weak modalities on multi-modal entity alignment, a Multi-modal Entity Alignment Method with Inter-modal Enhancement (MEAIE) is proposed. This method introduces a unique modality call...
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Ammar Mohsin Butt, Muhammad Haroon Yousaf, Fiza Murtaza, Saima Nazir, Serestina Viriri and Sergio A. Velastin
Human action recognition has gathered significant attention in recent years due to its high demand in various application domains. In this work, we propose a novel codebook generation and hybrid encoding scheme for classification of action videos. The pr...
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Shangyi Yan, Jingya Wang and Zhiqiang Song
To address the shortcomings of existing deep learning models and the characteristics of microblog speech, we propose the DCCMM model to improve the effectiveness of microblog sentiment analysis. The model employs WOBERT Plus and ALBERT to dynamically enc...
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Stefan Wagenpfeil, Felix Engel, Paul Mc Kevitt and Matthias Hemmje
To cope with the growing number of multimedia assets on smartphones and social media, an integrated approach for semantic indexing and retrieval is required. Here, we introduce a generic framework to fuse existing image and video analysis tools and algor...
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Konlakorn Wongpatikaseree, Sattaya Singkul, Narit Hnoohom and Sumeth Yuenyong
Language resources are the main factor in speech-emotion-recognition (SER)-based deep learning models. Thai is a low-resource language that has a smaller data size than high-resource languages such as German. This paper describes the framework of using a...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Lianlian He, Hao Li and Rui Zhang
Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeferen...
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Yunfei Zhang, Hongzhen Xu and Xiaojun Yu
An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborativ...
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Suping Wang, Ligu Zhu, Lei Shi, Hao Mo and Songfu Tan
Cross-modal retrieval aims to elucidate information fusion, imitate human learning, and advance the field. Although previous reviews have primarily focused on binary and real-value coding methods, there is a scarcity of techniques grounded in deep repres...
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Guozhe Yang, Qingze Tan, Zhiqiang Tian, Xingyu Jiang, Keqiang Chen, Yitao Lu, Weijun Liu and Peisheng Yuan
To cope with the problems of poor matching between processing characteristics and manufacturing resources, low production efficiency, and the hard-to-meet dynamic and changeable model requirements in multi-variety and small batch aerospace enterprises, a...
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Shiyu Lu, Huamin Yang and Cheng Han
Due to the often substantial size of the real-world point cloud data, efficient transmission and storage have become critical concerns. Point cloud compression plays a decisive role in addressing these challenges. Recognizing the importance of capturing ...
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Yingxiao Li, Ping Ma and Ju Huo
In the final approach stage of rendezvous and docking of a spacecraft, the pose parameters of the target spacecraft need to meet docking or berthing capture conditions. Visible light visual measurement systems are increasingly employed in spacecraft grou...
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Weijun Pan, Peiyuan Jiang, Zhuang Wang, Yukun Li and Zhenlong Liao
In recent years, the emergence of large-scale pre-trained language models has made transfer learning possible in natural language processing, which overturns the traditional model architecture based on recurrent neural networks (RNN). In this study, we c...
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Lingchong Zhong, Lijun He, Yongcui Li, Yu Zhang, Yong Zhou and Wenfeng Li
Heterogeneous quay cranes (HQCs) are the main energy-consuming equipment of automated container terminals, and they need to move from one bay to another along the rail and maintain a safe distance from one another. Improving the operational efficiency of...
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Junwei Chen, Yangze Liang, Zheng Xie, Shaofeng Wang and Zhao Xu
Building information models (BIMs) offer advantages, such as visualization and collaboration, making them widely used in the management of existing buildings. Currently, most BIMs for existing indoor spaces are manually created, consuming a significant a...
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Hua Yang, Xingquan Deng, Hao Shen, Qingfeng Lei, Shuxiang Zhang and Neng Liu
In recent years, the domain of diagnosing plant afflictions has predominantly relied upon the utilization of deep learning techniques for classifying images of diseased specimens; however, these classification algorithms remain insufficient for instances...
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Tiange Zhu, Raphaël Fournier-S?niehotta, Philippe Rigaux and Nicolas Travers
We address the problem of scalable content-based search in large collections of music documents. Music content is highly complex and versatile and presents multiple facets that can be considered independently or in combination. Moreover, music documents ...
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Junwen Lu, Jinhui Wang, Xiaojun Wei, Keshou Wu and Guanfeng Liu
There is relatively little research on deep learning for anomaly detection within the field of deep learning. Existing deep anomaly detection methods focus on the learning of feature reconstruction, but such methods mainly learn new feature representatio...
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