检索结果-内蒙古大学图书馆

2024 Symposium on Spatial Information to Empower the Metaverse

作者： Sun, Shangzhe Chen, Chi Yang, Bisheng Li, Liuchun Xu, Yuhang Jin, Ang State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application Ministry of Education of China China Institute of Artificial Intelligence in Geomatics Wuhan University Wuhan China Institute of Artificial Intelligence School of Computer Science Wuhan University Wuhan China

With the advancement of technology, unexposed spaces have emerged as a new type of strategic area, attracting significant attention from researchers. These spaces often present complex environments, such as extreme lighting variations, irregular geometries, and the lack of external positioning signals, making human entry hazardous. Fortunately, advancements in robotics and artificial intelligence have enabled unmanned systems to mitigate these challenges, allowing for safer exploration of unexposed spaces. UAVs, as vital unmanned system platforms, are extensively used across various industrial scenarios and are particularly effective for detecting unexposed spaces. To facilitate automated exploration of these areas, we propose the autonomous UAV system, LUOJIA Explorer. Equipped with a LiDAR sensor, data transmission module, and external anti-collision devices to protect the aircraft, LUOJIA Explorer is designed for effective unexposed space detection. We have integrated a laser point cloud positioning and mapping subsystem, along with a planning and control subsystem, into the LUOJIA Explorer. Through both simulation and actual experiments, the Luojia Explorer has demonstrated the capability to achieve stable flight based on self-positioning in unexposed spaces, with an exploration efficiency of 88.83 m3/s. © Author(s) 2024.

关键词： Aircraft accidents

来源：评论

学校读者我要写书评

暂无评论

Dynamic Textual Prompt For Rehearsal-free Lifelong Person Re-identification

arXiv

引用

arXiv 2024年

作者： Chen, Hongyu Jiao, Bingliang Wang, Wenxuan Wang, Peng Zhang, Yanning The National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an710060 China

Lifelong person re-identification attempts to recognize people across cameras and integrate new knowledge from continuous data streams. Key challenges involve addressing catastrophic forgetting caused by parameter updating and domain shift, and maintaining performance in seen and unseen domains. Many previous works rely on data memories to retain prior samples. However, the amount of retained data increases linearly with the number of training domains, leading to continually increasing memory consumption. Additionally, these methods may suffer significant performance degradation when data preservation is prohibited due to privacy concerns. To address these limitations, we propose using textual descriptions as guidance to encourage the ReID model to learn cross-domain invariant features without retaining samples. The key insight is that natural language can describe pedestrian instances with an invariant style, suggesting a shared textual space for any pedestrian images. By leveraging this shared textual space as an anchor, we can prompt the ReID model to embed images from various domains into a unified semantic space, thereby alleviating catastrophic forgetting caused by domain shifts. To achieve this, we introduce a task-driven dynamic textual prompt framework in this paper. This model features a dynamic prompt fusion module, which adaptively constructs and fuses two different textual prompts as anchors. This effectively guides the ReID model to embed images into a unified semantic space. Additionally, we design a text-visual feature alignment module to learn a more precise mapping between fine-grained visual and textual features. We also developed a learnable knowledge distillation module that allows our model to dynamically balance retaining existing knowledge with acquiring new knowledge. Extensive experiments demonstrate that our method remarkably outperforms SOTAs under various settings. Our model even outperforms rehearsal-based state-of-the-art approaches by

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

A Unified Representation Model and View Mapping Algorithm for Path-Mapping-Based Redirection Gains in Redirected Walking

A Unified Representation Model and View Mapping Algorithm fo...

引用

2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Bao, Xiyu Bian, Yulong Xin, Shiqing Qi, Meng Yang, Chenglei Shandong University Shandong Jinan China Shandong University Weihai China Shandong University Jinan China School of Information Science and Engineering Shandong Normal University Jinan China School of Computer Science & Technology Shandong University Jinan China Shandong Key Laboratory of Intelligent Electronic Packaging Testing and Application Weihai China

ISBN: (纸本)9798400713958

Among various redirected walking techniques, redirection gains guide users’ visual perception by introducing deviations between virtual and physical walking trajectories. This allows users wearing virtual reality headsets to explore a larger virtual space within a limited physical area. Current redirection gain manipulation methods primarily establish mapping relationships between virtual and physical paths, typically represented by straight lines or arcs, to align users’ physical and virtual perspectives. In this study, we propose a unified representation model and viewpoint mapping algorithm for path-mapping-based redirection gains. By inputting a few parameters, the model generates corresponding path mappings for various redirection gains, significantly simplifying the design and application of redirection gains. Furthermore, our viewpoint mapping algorithm effectively addresses mapping errors caused by dynamic gains in existing algorithms, which often lead to discontinuous trajectories and teleportation artifacts. This algorithm improves the continuity of the mapped trajectories and enhances the overall user experience during virtual exploration. © 2025 Copyright held by the owner/author(s).

关键词： Redirected walking Redirection gain representation model viewpoint mapping

来源：评论

学校读者我要写书评

暂无评论

Comparison of Tumor Segmentation Techniques from Medical Images 7

Comparison of Tumor Segmentation Techniques from Medical Ima...

引用

7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Gururaj, Bharathi Nair, Prajith Prakash Harish, L. Shanmugasundaram, V. Alaskar, Kamal Maranan, Ramya Ece Acs College of Engineering Karnataka India Cmr Institute of Technology Information Science and Engineering Karnataka India Sona College of Technology Department of Electrical and Electronics Engineering Chennai India Institute of Management Department of Computer Application Maharashtra Kolhapur India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350341485

A Brain Tumor (BT) is one of the leading causes of mortality worldwide. Because of this, early diagnosis is crucial. BT localization and segmentation from magnetic resonance imaging (MRI) is a challenging but crucial task with many medical analytic applications. Many methods have been presented for tumor segmentation. However, they each have their issues, such as reliance on manual intervention from experts and uncertainty over which feature extractor to use. To overcome these obstacles, a novel, hybrid strategy for tumor region segmentation based on a convolutional neural network is suggested. Kaggle's Brain MRI data was used for training and testing the proposed approach. First, a pre-processing strategy is used to operate on a selected portion of the image instead of the entire image to obtain a robust and adaptable BT segmentation system. Reduced processing time and no overfitting issues are the results of this strategy. Second, the Res-SegNet hybrid model was employed, now the model works only with a smaller portion of the MRI Accuracy, loss, Intersection of Union (IoU), and Dice coefficient are some of the metrics that were used to gauge how well the proposed method performed. When applied to tumor segmentation, the model achieved an accuracy of 0.99, an IoU of 0.745, a Dice of 0.831, and a loss of 0.176. © 2023 IEEE.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

A Conflicting Evidence Fusion Method Based on a Greedy Strategy

A Conflicting Evidence Fusion Method Based on a Greedy Strat...

引用

computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Haibo Li Jianyu Xiao Qi Tang School of Computer Science and Technology Huaibei Normal University Huaibei China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior Huaibei China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

To address the issue of the conventional D-S combination rule not effectively dealing with highly conflicting evidence fusion, a conflicting evidence fusion algorithm utilizing a greedy strategy is proposed. First, by adopting a greedy strategy, the effective evidence distance is defined based on Jousselme’s evidence distance, followed by the definition of strongly and weakly correlated evidence. The average value of the effective evidence distance is calculated, and based on this the evidence is classified. Finally, weights are calculated individually for the classified evidence. Weights are then reassigned to the two types of evidence, and the corrected evidence is fused to obtain the final fusion result. Numerical examples are provided to demonstrate the effectiveness of the method proposed in this paper in addressing the limitations of the conventional D-S combination rule for fusing highly conflicting evidence.

关键词： computer vision Correlation Evidence theory Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Innovative anti-phishing framework using machine learning approach with evolutionary optimization to secure multimedia applications

引用

Multimedia Tools and applications 2025年 1-28页

作者： Sharma, Bhawna Khurana, Savita Sharma, Gaurav Rani, Sunita Nandal, Sudesh Kumari Chandi, Pragya Rastogi, Rashi Castilla, Ángel Kuc Goyal, Nitin Department of Computer Science & Engineering JMIT Radaur India Department of Information Technology JMIT Radaur India Department of Computer Science & Engineering and Information Technology BPS Mahila Vishwavidalaya Sonipat India Department of Electronics and Communication Engineering BPS Mahila Vishwavidalaya Sonipat India Department of Computer Science & Engineering University Institute of Engineering and Technology Kurukshetra University Haryana India Department of Computer Application Sir Chhotu Ram Institute of Engineering and Technology CCS University Meerut India Engineering Research & Innovation Group Universidad Europea del Atlántico Santander Spain Department of Project Management Universidad Internacional Iberoamericana Campeche México Department of Project Management Universidad Internacional Iberoamericana Arecibo USA Department of Computer Science & Engineering School of Engineering and Technology Central University of Haryana Mahendergarh India

The transmission of users’ personal data via networks poses an increased risk of being exposed to phishing threats. Phishing URLs hiding malicious web addresses have become a widespread means of compromising user privacy. This paper is to improve the accuracy and efficiency of detecting and defending against phishing attacks in multimedia applications, aiming to safeguard users'personal data from exposure via phishing URLs. The proposed approach can be summarized in three phases. In the first phase, cosine and Jaccard similarities between training and test datasets are calculated to obtain a comprehensive understanding of the similarities of data points. A hybrid similarity score is built by combining these two measures in the second phase of the experiment to effectively blend content-related and quantity-related similarities. The third and final phase involves training a model on XGBoost that uses a hybrid similarity score as an input and then tunning up its hyperparameters using a genetic algorithm with the optimization of classification performance. Finally, the created powerful classifiers are merged to form a stacked ensemble model, increasing the overall accuracy of the classification. The strenuous test evaluation of 11,429 rows, 88 columns, through key metrics, such as Precision, Recall, F-Score, and Accuracy show that the proposed anti-phishing model has outperformance parameters in other models. With this lean approach, accuracy in classification can be improved by the incorporation of similarity-based techniques and machine learning and evolutionary optimization, in which defense can be performed against phishing threats in multimedia environments. The new innovation involved in the proposed work is based on stacking an ensemble of similarity-based techniques with a learning and optimization framework of machines, ensuring robustness toward phishing threat defense.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Leveraging UAV Technology for Enhanced Disaster Management: Innovations and applications

Leveraging UAV Technology for Enhanced Disaster Management: ...

引用

2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Upadhyay, Govind Murari Vats, Prashant Shanker, Surabhi Bhushan, Saloni Mittal, Sonu Mandot, Manju Manipal University Jaipur Dept. of Computer Application Rajasthan Jaipur India Manipal University Jaipur School of CSE Dept. of CSE Rajasthan Jaipur India K.R. Mangalam University School of Engineering & Technology Dept. of CSE Sohna Road Haryana Gurugram India Chhatrapati Shivaji Maharaj University Dept. of Computer Science/IT Maharashtra Panvel India Amity Institute of Information Technology Amity University Noida Dept. of CSE Uttar Pradesh India J. R. N. Rajasthan Vidyapeeth University Dept. of Computer Science/IT Rajasthan Udaipur India

ISBN: (纸本)9798350385199

Unmanned Aerial Vehicles (UAVs) have substantially advanced the sector by providing improved real-time monitoring, data collecting, and situational awareness capabilities when integrated into disaster management techniques. This study examines the creative uses of unmanned aerial vehicles (UAVs) in disaster relief, emphasising how they may speed up reaction times and increase operational effectiveness in emergency situations. With an emphasis on their usefulness in human detection, damage assessment, and coordination efforts, we propose a thorough framework that describes the design, deployment, and evaluation of UAV systems customised for catastrophe situations. The study shows how UAVs may be used to enhance processes of decision-making and enable more efficient recovery and catastrophe response through instances and quantitative evaluation. The results demonstrate how UAV technology may revolutionise conventional disaster management procedures and provide insightful information for future studies and real-world applications in the field. © 2024 IEEE.

关键词： Disaster prevention

来源：评论

学校读者我要写书评

暂无评论

Word-Constrained Response Generation for International Chinese Language Education based on Decoder Backward Attention 23

Word-Constrained Response Generation for International Chine...

引用

3rd International Conference on Artificial Intelligence, Automation and Algorithms, AI2A 2023

作者： Sun, Jingbo Song, Tianbao Liu, Haitao Peng, Weiming Song, Jihua School of Artificial Intelligence Beijing Normal University Beijing China School of Computer Science and Engineering Beijing Technology and Business University Beijing China Chinese Character Research and Application Laboratory Beijing Normal University Beijing China Linguistic Data Consortium University of Pennsylvania PhiladelphiaPA United States

ISBN: (纸本)9798400707605

Dialogue systems are a valuable technology in the field of natural language processing to improve work, learning, and daily life. Currently, dialogue systems are employed as an educational technology for mentoring, evaluation, and personalized learning. To make dialogue teaching achieve the purpose of training vocabulary at the primary level of international Chinese learning education, we first collect the entire dialogue corpus from textbooks to create the dataset, and then we propose a dialogue response generation model, Seq2BF-Attention, containing a specific word based on the sequence to backward and forward sequences framework by adding an attention to enhance the modeling of dialogue posts. We also provide two decoder connection strategies, backward hidden connection and backward attention, to handle the problems of not sharing parameters and incoherent generation separately. It has been experimentally proven that our suggested models perform well in both the ICLE and Weibo datasets across all metrics. © 2023 ACM.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

Exploiting Convolutional Neural Networks for Automated Pathology Image Classification

Exploiting Convolutional Neural Networks for Automated Patho...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Sunil Sharma C Menaka Akhilendra Pratap Singh Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. Automatic picture evaluation has become increasingly crucial to exploit those photographs for clinical selections. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized, and their capability applicability in pathology picture classification is discussed. This overview also introduces the maximum hit CNN methods that have been proposed and have proven promising consequences in pathology photograph category duties. The paper concludes with a dialogue of future research directions in this area. Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. To exploit those photographs for clinical selections, automatic picture evaluation has grown to be an increasingly number of crucial. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized,

关键词：

来源：评论

学校读者我要写书评

暂无评论

Prediction of Reliability of Data in Underwater Communication Network Using Fuzzy Logic

Prediction of Reliability of Data in Underwater Communicatio...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Surendra Yadav Gobi N Rakesh Kumar Yadav Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

This paper uses fuzzy logic to propose a reliability prediction set of rules for the underwater communication community. The set of rules uses fixed fuzzy rules to expect communication reliability among nodes in an underwater environment. Those fuzzy rules are derived from a reliability model based on the characteristics of an ordinary underwater conversation system, such as physical and environmental elements. The algorithm is then examined using accurate statistics from an underwater communication test. The effects imply that this approach is promising in predicting the reliability of the community. It has also been discovered that reliability prediction accuracy can be advanced if the bushy guidelines include extra factors, the sign channel's records rate, and the machine's performance parameters. This study offers a practical approach to improving the performance and reliability of underwater communique networks.

关键词：

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：