检索结果-内蒙古大学图书馆

24th International Arab Conference on information technology, ACIT 2023

作者： Irsan, Muhamad Hassan, Rosilah Abdali, Taj-Aldeen Naser Ishak, Mohamad Khairi School of Computing Telkom University Bandung Indonesia College of Engineering and Information Technology Ajman University Department of Information Technology United Arab Emirates University of Misan Faculty of Basic Education Misan62001 Iraq Ajman University Department of Electrical and Computer Engineering Ajman United Arab Emirates

ISBN: (纸本)9798350384307

Instances of COVID-19 transmission occur daily due to individuals failing to maintain distance or engaging in physical contact with others who may be contaminated with the virus. To mitigate this issue, this study has developed a system to detect human subjects practicing social distancing. The system utilizes a Raspberry Pi 4 Model B 8GB device in combination with a Logitech HD Webcam C270 camera. To detect human subjects, the Convolutional Neural Network is employed, utilizing the You Only Look Once (YOLO) method. In the testing phase of the tool, the system successfully identifies human subjects and assesses their proximity to others. It also detects instances of social distancing violations. The system achieved an average mean Average Precision (mAP) of 0.9792, a Precision of 0.9482, a Recall of 0.9819, and an f1 score of 0.9648. © 2023 IEEE.

关键词： COVID Image Raspberry Pi Social distancing YOLO

来源：评论

学校读者我要写书评

暂无评论

Integrity of Code and IoT Validation of Resource Utilization in Micro Control Unit

Integrity of Code and IoT Validation of Resource Utilization...

引用

2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Kushwaha, Ritesh Kumar Ravikumar, Parimi Lvd Mohammed, Muzammil H Sasthi Kumar, C. Chandigarh University Department of Electronics & Communication Engineering Punjab Mohali India Shri Vishnu Engineering College for Women Deparmnent of Information Technology Bhimavaram India Taif University Department of Information Technology Taif Saudi Arabia Karpagam Academy of Higher Education Department of Computer Science Coimbatore India

ISBN: (纸本)9798350317060

Cybersecurity for the Internet of Things is gaining more and more attention as the number of IoT devices has increased and the number of attack stargeting these devices continues to grow exponentially. However, the significant focus areas for security measures have been guaranteeing services' constant availability and protecting users' private data. But code integrity is not receiving the attention it deserves because these devices lack the horsepower to provide more robust safeguards. This issue necessitates more study into adapting standard procedures for code integrity to IoT gadgets. This paper describes a virtual machine-based technique for ensuring the correct execution of code on the Internet of Things. The feasibility of a virtual machine tailored to safeguard software during firmware upgrades is demonstrated here. The suggested method's low resource requirements on popular microcontrollers have been verified experimentally. The acquired findings prove that this secured technique for coding may work in practice. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

PNRITR:Research on Positive and Negative Entity Region Perception Methods for Image-Text Retrieval 36

PNRITR:Research on Positive and Negative Entity Region Perce...

引用

36th International Conference on Software engineering and Knowledge engineering, SEKE 2024

作者： Zhang, Zhiping Sun, Tao Zheng, Hongyan Liu, Hao Liu, Gengchen Yang, Zhi Wang, Xiaoyu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)1891706594

The aim of cross-modal image-text retrieval is to heighten comprehension and to create robust associations between visual and textual content. This process entails a mutual querying and synchronization across various data formats. While conventional techniques have seen enhancements via attention-based approaches, they frequently miss the dynamics between corresponding and non-corresponding entity areas within image-text pairs. These techniques, often fixated on aligning image entities with textual terms, can overlook the congruence of entity characteristics, leading to less accurate localization. This research introduces PNRITR, an innovative strategy for cross-modal retrieval that leverages label learning to discern attributes absent from images, broadening the scope beyond just positive entity areas. PNRITR has delivered notable advancements on the Flickr30K and MS-COCO datasets. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

Real-Time Reconstruction of 3D Space using Holographic Video 15

Real-Time Reconstruction of 3D Space using Holographic Video

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Deshpande, Vivek Anandha Silambarasan, D. Kalra, Hitesh Reena, R. Gupta, Shivangi Manjunath, C. Vishwakarma Institute of Technology Department of Computer Engineering Maharashtra Pune India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Karnataka Bangalore India

ISBN: (纸本)9798350370249

The real-time Reconstruction of 3-D space and the usage of holographic video entail the capture and processing of films that have a three-dimensional shape in them. The manner of capturing the 3-dimensional shape includes: using a camera with the functionality to seize and technique the holographic photograph in a composite format, taking multiple photos, merging them into one hologram. Then, the photographs are processed in real-time with the usage of laptop imaginative and prescient algorithms for function extraction, segmentation, and 3-D object popularity. This application of the laptop, imaginative and prescient, allows the person to navigate and engage with the three-D illustration that is reconstructed in actual time. The reconstructed 3D scene is then rendered in the shape of an interactive 360-degree holographic video. This technology can provide a couple of applications in augmented and virtual reality gaming and immersive 3-D visualization of the captured environment. © 2024 IEEE.

关键词： Holograms

来源：评论

学校读者我要写书评

暂无评论

Enabling Scalable Applications with Intelligent Distributed Data Processing 2

Enabling Scalable Applications with Intelligent Distributed ...

引用

2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Mandela, Nelson Alam, Intekhab Amudha, A. Sirija Priyanka, D. Singh, Dhiraj Kumar Department of Animation and Virtual Reality Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350308846

This paper discusses the enabling of scalable programs with smart disbursed information processing. Scaling programs can be challenging, mainly when dealing with massive datasets. Existing scaling answers often rely on conventional database-reliant architectures, which usually require massive manual attempts and significant investments in hardware and software. Clever dispensed information processing offers an alternative technique to scalability. With this technique, facts can be processed successfully and with accelerated degrees of automation using intelligent algorithms and distributed computing. This paper presents a top-level view of the ideas in the back of slick disbursed information processing and examines the benefits and challenges associated with this technique. Key ideas addressed in this paper include using utility-precise AI algorithms, dispensed computing, and data correlations. Sooner or later, the report highlights the critical trade-off between scalability and cost regarding the usage of wise disbursed statistics processing. © 2023 IEEE.

关键词： Computing Conventional information Scalability Technique

来源：评论

学校读者我要写书评

暂无评论

Advancing Blackboard Framework: Responsive Trigger Mechanisms and Dynamic Feasibility Conditions for Optimal Knowledge Source Selection 19

Advancing Blackboard Framework: Responsive Trigger Mechanism...

引用

19th International Conference on Ubiquitous information Management and Communication, IMCOM 2025

作者： Muhd Mukhtar, Hana Munira Husin, Husna Sarirah Ismail, Suriana Rahmat, Azizah Ismail, Roslan Software Engineering Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia School of Computer Science Taylor’s University Kuala Lumpur Malaysia Centre of Innovative Digital Education & Emerging Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

Expert systems (ES) rely heavily on effective control mechanisms to navigate complex problem-solving tasks. These mechanisms govern how ES utilizes knowledge and data to make decisions and execute actions. Optimizing these mechanisms, or addressing the "control problem," remains a central challenge. Blackboard architectures, with their separation of knowledge and control processes, offer a promising approach. This study introduces an improved control mechanism for blackboard architectures. It focuses on a critical aspect—trigger mechanisms and feasible conditions—for optimal knowledge source selection to participate in the problem-solving process. By leveraging these features, this study aims to enhance decision-making and problem-solving capabilities within complex domains. This paper focuses on the technical details of exploring how it manages the flow of rule activation and execution throughout the problem-solving process. © 2025 IEEE.

关键词： Expert systems

来源：评论

学校读者我要写书评

暂无评论

Customized Transformer Adapter with Frequency Masking for Deepfake Detection

引用

IEEE Transactions on information Forensics and Security 2025年 20卷 5904-5918页

作者： Shi, Zenan Chen, Haipeng Jia, Yixin Zhang, Dong Lu, Wei Yang, Xun Jilin University College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Jilin University College of Software Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Sun Yat-sen University School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Guangzhou510006 China University of Science and Technology of China School of Information Science and Technology Hefei230026 China

The evolution of advanced artificial intelligence generated content approaches has heightened concerns about deepfake, due to the sophisticated forgeries and concealed appearances they produce. To this end, the pre-trained Vision Transformer (ViT) model has become a de facto choice for deepfake detection, thanks to its powerful learning capability. Despite favorable results achieved by existing ViT-based methods, they have inherent limitations that could result in suboptimal performance in scenarios with continuously evolving forgery techniques, such as overfitting to single forgery patterns or placing excessive emphasis on dominant forgery regions. In this paper, we propose CUTA, a simple yet effective deepfake detection paradigm that utilizes ViT adapters as the medium and fully exploits the spatial- and frequency-domain features of given images to overcome the limitations of existing methods. Specifically, CUTA focuses on frequency domain masking within the input space, which obscures parts of the high-frequency image to intensify the training challenge while preserving subtle forgery cues in the frequency domain to facilitate comprehensive forgery representations. Furthermore, we propose two task-customized modules within the ViT model, i.e., the texture enhancement module and the multi-scale perceptron module, to seamlessly integrate local texture and rich contextual features. These two modules ensure an organic interaction between the task-specific forgery patterns and general semantic features within the pre-trained ViT framework. The experimental results on several publicly available benchmark datasets demonstrate CUTA’s superiority in performance, particularly showcasing its significant advantages in both cross-dataset and cross-manipulation scenarios. 2005-2012 IEEE.

关键词： Frequency response

来源：评论

学校读者我要写书评

暂无评论

Automated Leukaemia Prediction and Classification Using Deep Learning Techniques 2

Automated Leukaemia Prediction and Classification Using Deep...

引用

2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Narendran, M. Amarendra, K. Revathy, D. Divyapushpalakshmi, M. Sharma, Dilip Kumar Upreti, Kamal Kcg College of Technology Department of Information Technology Tamil Nadu Chennai India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522502 India Karpaga Vinayaga College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chengalpet India Gitam University Department of Computer Science and Engineering Bengaluru561203 India Jaypee University of Engineering and Technology Department of Mathematics Madhya Pradesh Guna473226 India Department of Computer Science Delhi -NCR Ghaziabad India

ISBN: (纸本)9798350369960

Leukemia is typically diagnosed based on an abnormal blood count, frequently an elevated White Blood Cell (WBC) count. The diagnosis is established through bone marrow, replaced by neoplastic cells. Acute Lymphoblastic Leukemia (ALL) is a type of leukaemia that affects the blood and bone marrow. Leukaemia primarily affects children and adults around the world. Early leukaemia detection is critical for appropriately treating patients, especially children. This research aims to present a diagnostic method that uses computational intelligence and image processing algorithms to identify blast cells from ALL images. The medical image is prepared initially using the preprocessing and segmentation technique for efficient classification. In this research, the type is accomplished using Bidirectional Associative Memory Neural Networks (BAMNN), where the accuracy is 96.87%, the highest classification rate and outperforms the existing technique. © 2023 IEEE.

关键词： accuracy activation function and associative memory bone marrow classification DL Leukaemia neural network neurons

来源：评论

学校读者我要写书评

暂无评论

The Use of 6G Communication technology in Healthcare Applications for the Accurate and Better Transmission 4

The Use of 6G Communication Technology in Healthcare Applica...

引用

4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Omkar, Jamvant Menaka, S. Praveena, J. Varshney, Neeraj Arunkumar, B. Reddy, G. Vinoda Ies College of Technology Department of Electronics & Communication Engineering M. P Bhopal India Nehru Institute of Information Technology and Management Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Hummanities TN India Gla University Department of Computer Engineering and Applications Mathura India Karpagam Academy of Higher Education Computer Science Engineering Department India Hyderabad Medchal India

ISBN: (纸本)9798350360165

The IIoT is the most important element in the 6th generation networks, or 6G, so it greatly depends on effective data processing and storage. For the cause of ensuring smooth node-to-node communication, 6G provides ultra-low delays, high bandwidth, and higher-level QoS. Intelligent diagnosis, numerous in-hospital, and distant healthcare services are prerequisites to enable healthcare institutions to provide patientcentered care. What is essential is that the system hosting an array of uses, ranging from ambient appropriate living settings with wearable technology-enabled remote patient monitoring to robotic procedures powered by an intelligent networking platform. Therefore, this work addresses the needs of the healthcare sector by providing a reference-layered contact architecture for locations and devices in real-time communication. The unique 6G technology can, therefore, be utilized with great foresight to the future in the healthcare sector, enabling effective treatment and intelligent service integration. Because several networking nodes, including terminal devices, are integrated into effective health service delivery, a backbone structure is thus required for the services that take much time to complete. Therefore, a backbone structure for managing services is required to enable smooth communication by the framework, developed to enable this kind of 6G-enabled advanced healthcare application. © 2024 IEEE.

关键词： Remote patient monitoring

来源：评论

学校读者我要写书评

暂无评论

ElephantGuardNet: A Comprehensive Solution for Elephant Conservation and Human-Elephant Conflict Reduction 4

ElephantGuardNet: A Comprehensive Solution for Elephant Cons...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Naveen, S. Dhamotharan, R. Sahebzathi, S. Krishnan, R. Santhana Kumar, V. Vinoth Sundaravadivel, P. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Mechanical Engineering Chennai India Kalasalingam Academy of Research and Education Department of Computer Science and Information Technology Krishnankoil India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798331523923

The ElephantGuardNet system is an advanced technological framework designed to monitor and protect elephants while minimizing human-elephant conflict. The system leverages a combination of real-time data collection, AI-driven analysis, and IoT sensors to track elephant movements across vast territories. By integrating wildlife camera traps, drones, satellite imagery, and IoT sensors such as infrared motion detectors and seismic sensors, the system provides continuous monitoring of elephant activity, enabling proactive management of potential risks. A custom dataset, ElephantMovementTracker, compiled from diverse data sources, forms the foundation for the model's training. Preprocessing techniques such as data normalization, augmentation, and noise filtering enhance the dataset's quality and ensure its suitability for deep learning applications. EfficientNet B7 and YOLO are employed for image and real-time detection tasks, respectively, while 3D CNNs are used for video analytics, enabling accurate tracking of dynamic movement patterns. GRU-based models predict future elephant movements, helping assess the likelihood of conflict. XGBoost is utilized for classification tasks, evaluating the risk of human-elephant conflict. The system is deployed on AWS and incorporates NVIDIA Jetson Nano for real-time detection and automated alerting via SMS and email. IoT sensors and automated deterrent systems, including sound emitters and drones, further mitigate conflict risk. The system's effectiveness in reducing human-elephant conflicts and providing a scalable solution for elephant conservation demonstrates the potential of AI and IoT integration in wildlife protection efforts, offering a comprehensive approach to both conservation and human-elephant coexistence. © 2025 IEEE.

关键词： Drones

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：