检索结果-内蒙古大学图书馆

Medical knowledge graph question answering for drug-drug interaction prediction based on multi-hop machine reading comprehension

引用

CAAI Transactions on Intelligence Technology 2024年第5期9卷 1217-1228页

作者： Peng Gao Feng Gao Jian-Cheng Ni Yu Wang Fei Wang Qiquan Zhang School of Cyber Science and Engineering Qufu Normal UniversityQufuChina School of Computer Science and Technology East China Normal UniversityShanghaiChina Network and Information Center Qufu Normal UniversityQufuChina School of Electronics and Information Engineering Harbin Institute of TechnologyShenzhenChina School of Electrical Engineering and Telecommunications University of New South WalesSydneyNSWAustralia

Drug-drug interaction(DDI)prediction is a crucial issue in molecular *** methods of observing drug-drug interactions through medical experiments require significant resources and *** authors present a Medical Knowledge Graph Question Answering(MedKGQA)model,dubbed MedKGQA,that predicts DDI by employing machine reading comprehension(MRC)from closed-domain literature and constructing a knowledge graph of“drug-protein”triplets from open-domain *** model vectorises the drug-protein target attributes in the graph using entity embeddings and establishes directed connections between drug and protein entities based on the metabolic interaction pathways of protein targets in the human *** aligns multiple external knowledge and applies it to learn the graph neural *** bells and whistles,the proposed model achieved a 4.5%improvement in terms of DDI prediction accuracy compared to previous state-of-the-art models on the QAngaroo MedHop *** results demonstrate the efficiency and effectiveness of the model and verify the feasibility of integrating external knowledge in MRC tasks.

关键词： artificial neural network data analysis document handling natural language processing

来源：评论

学校读者我要写书评

暂无评论

LASS: A Novel and Economical Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization 31

LASS: A Novel and Economical Data Augmentation Framework Bas...

引用

31st International Conference on Computational Linguistics, COLING 2025

作者： Zhang, Yanyue Li, Pengfei Lai, Yilong He, Yulan Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King's College London United Kingdom The Alan Turing Institute United Kingdom

ISBN: (纸本)9798891761964

As more than 70% of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are hesitant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the reliance on a specific structure is to generate additional data based on large language models to balance the emotional distribution of the dataset. However, large-scale data augmentation based on large language models faces an apparent disadvantage, the expensive costs. Therefore, in this paper, we propose LASS, a novel data augmentation framework based on both LArge and Small language models for debiaSing opinion summarization. Specifically, a small number of synthesized negative reviews is obtained by rewriting the positive text via a large language model. Then, a disentangle reconstruction model is trained based on the generated data. After training, a large amount of synthetic data can be obtained by decoding the new representation obtained from the combination of different sample representations and filtering based on perplexity degree and sentiment classification. Experiments have proved that LASS can effectively alleviate emotional bias, similar to using only large models, but in a more economical way. © 2025 Association for Computational Linguistics.

关键词： Data assimilation

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Perturbed Secret Sharing Federated Learning Framework 6

A Hybrid Perturbed Secret Sharing Federated Learning Framewo...

引用

6th International Conference on Next Generation Data-Driven networks, NGDN 2024

作者： Feng, Yinglin Chen, Shuhong Cheng, Zhaoyi Su, Weifeng Wang, Tian Guangzhou University School of Computer Science and Network Engineering Guangzhou China Beijing Normal University BNU-UIC Institute of Artificial Intelligence and Future Networks Beijing China

ISBN: (纸本)9798350388374

In recent years, the problem of privacy leakage in federated learning has received much attention. To address this issue, researchers have applied privacy preserving techniques to federated learning. However, differential privacy adding too much noise can affect the generalization of the model and the availability of data. Secret sharing may also lead to data leakage if attacked. In order to tackle the problems of excessive noise and data security, this paper proposes a hybrid perturbation secret sharing federated learning framework (HPS-FL). It optimizes local difference privacy based on mean statistics and mitigates the effect of excessive noise by changing the perturbation boundary and reducing the variance. It also introduces secret sharing technology, which further increases the security of parameter transmission by adding a mask before secret sharing. Experimental results on the MINIST dataset demonstrate that HPS-FL outperforms other methods in terms of model accuracy, providing reliable support for privacy preserving. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Robust Facial Emotion Recognition System via De-Pooling Feature Enhancement and Weighted Exponential Moving Average

Robust Facial Emotion Recognition System via De-Pooling Feat...

引用

2024 IEEE Region 10 Conference, TENCON 2024

作者： Win, Khin Cho Akhtar, Zahid Mohan, C. Krishna Indian Institute of Technology Dept. of Artificial Intelligence Hyderabad India State University of New York Polytechnic Institute Dept. of Network and Computer Security UticaNY United States Indian Institute of Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350350821

Facial expression recognition (FER) in an uncontrolled environment presents a formidable challenge in affective computing and human-machine interaction domains. Existing FER models fail to generalize due to the innate expression nature of the intra-class separability and inter-class compactness. Although most state-of-the-art FER research focuses on more advanced frameworks and well-separated discriminative loss functions, further exploration is needed to obtain high-quality expression features. This paper proposes a robust feature enhancement approach for FER by integrating the De-pooling Feature Enhancement and Weighted Exponential Moving Average (WEMA) of Stochastic Gradient Descent (SGD). The proposed method utilizes De-Pooling Feature Enhancement to capture and enhance the high-quality expression features, while WEMA of SGD optimizes the training process for improved stability and convergence. Our extensive experimental analysis of benchmark datasets signifies that our proposed method prevails over state-of-the-art methods, achieving superior accuracy performances of 86.43% on FER2013, 94.97% on FERPlus, 94.71% on RAF-DB, as well as 80.62% and 72.90% on AffectNet, of 7 class and 8 class, respectively. © 2024 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

APPLICATION OF KUSHO RECOGNITION TECHNOLOGY TO INFORMATION MANAGEMENT IN RESTAURANT KITCHENS 50

APPLICATION OF KUSHO RECOGNITION TECHNOLOGY TO INFORMATION M...

引用

50th International Conference on computers and Industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Usuki, Risa Usuki, Jun Department of Computer Science and Engineering Waseda University Tokyo Japan Department of Information Network and Communication Kanagawa Institute of Technology Kanagawa Japan

ISBN: (纸本)9781713886952

With the advancement of information technology, research on non-contact methods as well as contact methods using keyboards and controllers as methods of operating devices has been progressing. One such method is handwriting characters in the air (hereinafter called "KUSHO"), which allows users to input information to devices through characters written in the air. KUSHO enables users to transmit information by writing characters towards a camera. It involves three steps: tracking hand movements from camera images, converting tracking information into features, and recognizing input information from features. KUSHO offers advantages such as non-contact operation without special devices and intuitive operation using familiar characters. By the way, in a kitchen, workers confirm orders and cooking procedures, operate cooking equipment and transmit information between processes. Additionally, although display devices are used to transmit information in large-scale restaurants, the use of devices is not suitable for tasks that involve dirty hands due to hygiene concerns. Paper-based communication is also used, however, it can easily get dirty in a kitchen with water and oil. In addition, the use of voice dictation, which has been developed in recent years as a non-contact operation method, is difficult due to its tendency to generate noise, and considering the diversification of customer demands, it is necessary to consider new support methods in terms of information handling. Therefore, this study proposed a method of applying KUSHO in restaurant kitchens, where quick communication is necessary while maintaining hygiene. Following this, the proposed methods were implemented and their potential was discussed through a comparison of recognition rates between different methods, and experiments of command input by signals during KUSHO and KUSHO input for information management assuming kitchens. © 2023 computers and Industrial engineering. All rights reserved.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Pedestrian and Vehicle Detection Based on Pruning YOLOv4 with Cloud-Edge Collaboration

引用

computer Modeling in engineering & Sciences 2023年第11期137卷 2025-2047页

作者： Huabin Wang Ruichao Mo Yuping Chen Weiwei Lin Minxian Xu Bo Liu School of Computer Science and Engineering Huizhou UniversityHuizhou516007China School of Computer Science and Engineering South China University of TechnologyGuangzhou510006China School of Computer Science and Technology South China Normal UniversityGuangzhou510631China Department of New Network Technologies Peng Cheng LaboratoryShenzhen518066China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen518055China

Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile ***,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy *** addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge ***,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model *** results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher ***,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.

关键词： Pedestrian and vehicle detection YOLOv4 channel pruning cloud-edge collaboration

来源：评论

学校读者我要写书评

暂无评论

Double-branch fusion network with a parallel attention selection mechanism for camouflaged object detection

引用

Science China(Information Sciences) 2023年第6期66卷 258-266页

作者： Junjiang XIANG Qing PAN Zhengrong ZHANG Songnian FU Yuwen QIN Advanced Institute of Photonics Technology School of Information EngineeringGuangdong University of Technology Guangdong Provincial Key Laboratory of Photonics Information Technology Guangdong University of Technology Guangxi Key Laboratory of Multimedia Communications and Network Technology School of Computer Electronics and InformationGuangxi University

To meet the challenge of camouflaged object detection （COD）,which has a high degree of intrinsic similarity between the object and background,this paper proposes a double-branch fusion network（DBFN）with a parallel attention selection mechanism （PASM）.In detail,a schismatic receptive field block（SRF）combined with an attention mechanism for low-level information is performed to learn texture features in one branch,and an integration of the SRF,a hybrid attention mechanism （HAM）,and a depth feature polymerization module （DFPM）is employed for high-level information to extract detection features in the other ***,both texture features and detection features are input into the PASM to acquire selective expression ***,the final result is obtained after further selective matrix optimization with atrous spatial pyramid pooling （ASPP）and a residual channel attention block （RCAB）being applied *** results on three public datasets verify that our method outperforms the state-of-the-art methods in terms of four evaluation metrics,i.e.,mean absolute error （MAE）,weighted F βmeasure （Fβω）,structural measure （Sα）,and E-measure （Eφ）

关键词： camouflaged object detection attention mechanism feature extraction feature aggregation texture information fuzzy boundary

来源：评论

学校读者我要写书评

暂无评论

Dynamic Visible Light Positioning Based on Enhanced Visual Target Tracking

引用

China Communications 2023年第10期20卷 276-291页

作者： Xiangyu Liu Jingyu Hao Lei Guo Song Song School of Information Science and Engineering Shenyang Ligong UniversityShenyang 110158China Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China School of Computer Science and Engineering Northeastern UniversityShenyang 110819China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Hangzhou Institute of Advanced Technology Hangzhou 310056China Institute of Intelligent Communications and Network Security Chongqing University of Posts and TelecommunicationsChongqing 400065China

In visible light positioning systems,some scholars have proposed target tracking algorithms to balance the relationship among positioning accuracy,real-time performance,and ***,there are still two problems:(1)When the captured LED disappears and the uncertain LED reappears,existing tracking algorithms may recognize the landmark in error;(2)The receiver is not always able to achieve positioning under various moving *** this paper,we propose an enhanced visual target tracking algorithm to solve the above ***,we design the lightweight recognition/demodulation mechanism,which combines Kalman filtering with simple image preprocessing to quickly track and accurately demodulate the ***,we use the Gaussian mixture model and the LED color feature to enable the system to achieve positioning,when the receiver is under various moving *** results show that our system can achieve high-precision dynamic positioning and improve the system’s comprehensive performance.

关键词： visible light positioning visual target tracking gaussian mixture model kalman filtering system performance

来源：评论

学校读者我要写书评

暂无评论

Secure Rotation Invariant Face Detection System for Authentication

引用

computers, Materials & Continua 2022年第1期70卷 1955-1974页

作者： Amit Verma Mohammed Baljon Shailendra Mishra Iqbaldeep Kaur Ritika Saini Sharad Saxena Sanjay Kumar Sharma Department of Computer Science&Engineering Chandigarh Group of CollegesMohali140317India Department of Computer Engineering College of Computer&Information ScienceMajmaah University11952Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering&TechnologyPatiala147004India Department of Computer Centre&Campus Network Facility Science Complex PO Central UniversityGachibowliHyderabad500046TelanganaIndia

Biometric applications widely use the face as a component for recognition and automatic *** rotation is a variable component and makes face detection a complex and challenging task with varied angles and *** problem has been investigated,and a novice algorithm,namely RIFDS(Rotation Invariant Face Detection System),has been *** objective of the paper is to implement a robust method for face detection taken at various *** to achieve better results than known algorithms for face *** RIFDS Polar Harmonic Transforms(PHT)technique is combined with Multi-Block Local Binary Pattern(MBLBP)in a hybrid *** MBLBP is used to extract texture patterns from the digital image,and the PHT is used to manage invariant rotation *** this manner,RIFDS can detect human faces at different rotations and with different facial *** RIFDS performance is validated on different face databases like LFW,ORL,CMU,MIT-CBCL,JAFFF Face Databases,and Lena *** results show that the RIFDS algorithm can detect faces at varying angles and at different image resolutions and with an accuracy of 99.9%.The RIFDS algorithm outperforms previous methods like Viola-Jones,Multi-blockLocal Binary Pattern(MBLBP),and Polar HarmonicTransforms(PHTs).The RIFDS approach has a further scope with a genetic algorithm to detect faces(approximation)even from shadows.

关键词： Pose variations face detection frontal faces facial expressions emotions

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Distance Estimation Using Phase Information of OFDM Signal 100

Evaluation of Distance Estimation Using Phase Information of...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Liu, Jingwei Kikuchi, Noriyasu Kubo, Nobuaki Tang, Suhua The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan Kanagawa Institute of Technology Department of Mechanical Engineering Kanagawa Japan Tokyo University of Marine Science and Technology Information and Communication Engineering Laboratory Tokyo Japan

ISBN: (纸本)9798331517786

In urban areas, due to the obstruction/reflection of GNSS signals by roadside buildings, position accuracy is greatly degraded, or even outage occurs when no enough satellites are available. To address this problem, vehicles and roadside units have been used as positioning anchors to estimate pedestrian position. Although previous methods exploited channel state information, which is superior to received signal strength for distance estimation, they rely on signal attenuation characteristics, and the accuracy is limited by temporal resolution and multipath propagation. This work focuses on using the phase information of V2X OFDM signals to estimate distance differences more robustly. We investigated the impact of the sampling rate, a crucial parameter, and conducted simulation evaluations using 3D maps and ray-tracing. Additionally, we built a testbed and performed evaluations with real-world OFDM signal data, which demonstrates that phase information can significantly improve the accuracy of distance measurements. © 2024 IEEE.

关键词： Frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：