检索结果-内蒙古大学图书馆

2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Mourya, Gojja Sree Jami, Abhinav Ajith, Abhinav Seikh, Ayan Habib Kumar, J. Sathish Motilal Nehru National Institute of Technology Dept. of Computer Science and Engineering Allahabad India

ISBN: (纸本)9798350348460

In the disaster-affected area, whether it's a search and rescue operation, mock drill, managing food distribution, issuing warnings or anything else, the key to successfully carrying out these activities is preparation. To ensure that plans are accurate, one needs to know what actually happened in the disaster-affected area and for this purpose thoroughly and quickly the entire area need to be studied. To address this issue, we use UAV or drone navigation autonomously in required trajectories. By using UAVs you can cover surveillance across the vast acres of land quickly and know what happened and plan rescue operations accordingly. In this paper, we presented our work on moving the drones in multiple trajectories and swarm, thus amplifying surveillance capabilities. Each trajectory is maneuvered autonomously and a corresponding trajectory-algorithm running at the back end is presented along with the simulation results. © 2024 IEEE.

关键词： Disaster management Drones Multi-Agent systems Surveillance Swarm Trajectories Unmanned Aerial Vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Advanced Deep Learning Driven Geospatial Analysis for GLOF Risk Reduction: A Case Study from Pakistan’s Northern Mountain Ranges

Advanced Deep Learning Driven Geospatial Analysis for GLOF R...

引用

2024 International Conference on Frontiers of Information technology, FIT 2024

作者： Murad, Nauman Ali Mir, Abinta Mehmood Shahzadi, Nazia Faculty of Computer Science Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Topi Pakistan

ISBN: (纸本)9798331510503

Glacial Lake Outburst Floods (GLOFs) pose a severe risk to populations in high-altitude areas, particularly in Pakistan's northern regions, where glacier melt has created 3,044 glacial lakes in Gilgit-Baltistan and Khyber Pakhtunkhwa [1]. The Chitral region is especially vulnerable, highlighting the need for robust monitoring and mitigation strategies. This paper focuses on using Deep Learning (DL) models for detecting and segmenting glacial lakes to mitigate GLOF risks. Using the Glacial Lakes Detection Dataset from High-Mountain Asia, covering 2080.12 km2 and including around 30,121 glacial lakes, we selected 1,200 cloud-free true-color images with ground truth masks. Our study evaluates DL models like DeepLabV3+, UNet, and YOLOv8 for lake segmentation and classification. Experimental results demonstrated model proficiency, with DeepLabV3+ (ResNet50 backbone and Dice loss function) achieving the highest IoU score of 77.2%. These findings highlight the potential of DL-based systems for enhanced GLOF monitoring and early warning. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Wearable Sensor-Based Gait Analysis: Advanced Feature Extraction Techniques 2

Wearable Sensor-Based Gait Analysis: Advanced Feature Extrac...

引用

2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Karthik Salian, Preethi K. Ranjith, H.D. Salian, Supriya Jayashree Shetty, K. Annapoorneshwari NMAM Institute of Technology Udupi Nitte India NMAM Institute of Technology Udupi Nitte India Dept. of Electronics and Communication Engineering Mangalore Institute of Technology and Engineering Moodabidri India Dept. of Computer Science and Engineering St. Joseph Engineering College Mangaluru India Dept. of Computer Science and Engineering NM Institute of Technology Bangalore India Mangalore India

ISBN: (纸本)9798350383867

Gait irregularities among adults are common in clinical settings and can result in severe consequences such as falls and injuries, leading to increased healthcare costs. Presently, gait evaluation primarily relies on subjective assessments using standardized clinical tools. Although motion capture systems like Qualisys and Vicon offer more objective analysis, they depend on costly, intricate equipment in specialized gait laboratories. Due to limited accessibility, involving factors like equipment scarcity, demand for technical expertise, in-person patient visits, complex procedures, and high costs, these methods remain largely inaccessible. Consequently, there is a pressing need for a more objective and cost-effective gait assessment solution. The proposed work introduces an economical automated feature extraction approach to address this issue. Leveraging Inertial Measurement Unit (IMU) sensors, comprising a three-axis gyroscope and accelerometer system captures precise foot position and orientation data crucial for comprehensive gait analysis. IMU sensors have gained popularity due to their adaptability in clinical environments and non-clinical settings like patient residences or community spaces. With the help of a microcontroller mounted on the barefoot, the IMU sensor collects raw gyroscope and accelerometer data for gait analysis. These data are wirelessly transmitted via Bluetooth to a computer for subsequent in-depth analysis, enabling effective feature extraction for comprehensive gait assessment. © 2024 IEEE.

关键词： Accelerometers

来源：评论

学校读者我要写书评

暂无评论

An effective object detection via BS2ResNet and LTK-Bi-LSTM

引用

Multimedia Tools and Applications 2025年 1-20页

作者： V, Arulalan V, Premanand Kumar, Dhananjay Department of Computing Technologies SRM Institute of Science and Technology Chengalpattu District Tamil Nadu Kattankulathur603203 India Department of Computer Science and Engineering Vellore Institute Technology Chennai Campus Tamil Nadu Chennai India Department of Information Technology Anna University MIT Campus Tamil Nadu Chennai India

Video analytics faces complex challenges in object detection and classification. Deep learning based approaches have achieved remarkable success in past decade. However, existing object identification models that utilize backbone’s core features still present challenges due to their lack of semantic information. To address these issues, a novel object detection and classification framework utilizing Batch normalization and Softswish activation adapted ResNet (BS2ResNet) and Logistic Tanh Kaiming Bi-directional Long Short Term Memory (LTK-Bi-LSTM) techniques was proposed. The framework employs frame conversion, noise removal, and contrast elevation during frame pre-processing, followed by background subtraction using the Supreme Distance-centered Fuzzy C-Means (SD-FCM) clustering algorithm, and edge detection using the Hyperbolic Tangent Kernel Canny Edge Detector (HTKCED). BS2ResNet is then used for object detection, and features are extracted and passed to the LTK-Bi-LSTM neural network for object classification. The proposed system was found to improve object detection and classification accuracy, outperforming existing techniques. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

End-to-End Scene Text Detection and Recognition Based on Feature Interaction 6

End-to-End Scene Text Detection and Recognition Based on Fea...

引用

6th International Conference on Robotics and computer Vision, ICRCV 2024

作者： Luo, Die Yu, Qiuhui He, Chengwan Chen, Wei School of Computer Science and Engineering School of Artificial Intelligence Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798331527426

The present scene text extraction methods generally include two independent steps of text detection and text recognition, which is not beneficial to the interaction of feature information and may result in the accumulation of errors. Aiming at the above problems, an algorithm is proposed to achieve end-to-end text extraction by interacting information between text detection and recognition. In the process of extracting scene text, Swin-Transformer and CE-FPN are adopted as the base network to extract abundant feature representations at various scales which reduce the impact of information loss on text detection and recognition;Using Recognition Conversion to guide text localization by recognition loss enables feature interaction of detection and recognition;CTC is utilized in recognition to achieve the constraint of Attention decoding, which guarantees the full extraction of long text character information. Experimental results on several datasets show that the method in this paper demonstrates better performance compared to the existing typical models. © 2024 IEEE.

关键词： Text mining

来源：评论

学校读者我要写书评

暂无评论

Method for background replacement of certification photos

Method for background replacement of certification photos

引用

2024 International Conference on Optics, Electronics, and Communication engineering, OECE 2024

作者： Chen, Xu Zhang, Jihong Du, Yufei Sha, Zihuan Qiu, Rongfei Xu, Zezhong School of Computer Science and Information Engineering Changzhou Institute of Technology Jiangsu Changzhou213032 China

ISBN: (纸本)9781510685437

In order to overcome defects resulted from replacing the photo background color, an improved method is proposed for background replacement. The α-values in the alpha matte are transformed to enhance the details in the transition area. The new photo is composited by comprehensively considering the foreground portrait, new background, old background and the alpha matte. The experimental results show that the foreground portrait appears clearer and more complete, and the transition area between the foreground and background is more harmonious and more natural. © 2024 SPIE.

关键词： Color Opacity computer science engineering Image processing Image processing algorithms and systems Image processing software Image segmentation Information science

来源：评论

学校读者我要写书评

暂无评论

A High Gain Wide Band Compact Size Dual Band Patch Antenna for 5G Applications

A High Gain Wide Band Compact Size Dual Band Patch Antenna f...

引用

2023 IEEE International Conference on Emerging Trends in engineering, sciences and technology, ICES and T 2023

作者： Azam, Tahir Tahir, Farooq Ahmed Sarwar, Asima Qayyum, Muhammad Aqib National University of Science and Technology School of Electrical Engineering and Computer Science Islamabad Pakistan GIK Institute of Engineering Sciences and Technology Faculty of Computer Science and Engineering Topi Swabi Pakistan

ISBN: (纸本)9781665455602

This paper presents a high gain, compact size and dual band rectangular patch antenna for 5G applications. To enhance the gain of antenna, an equilateral triangle slots on the upper rectangular patch are constructed. The broadband antenna is operating at 27.4 GHz to 35.5 GHz and 38GHz to 41.8GHz having fractional bandwidth of 25.7% and 9% respectively. The maximum gain of 8.19 dBi is observed at 28 GHz and the antenna has radiation efficiency greater than 90% over the entire band. Moreover, the Voltage Standing Wave Ratio (VSWR) is lower than 2 dB at operational bands. © 2023 IEEE.

关键词： Radiation efficiency

来源：评论

学校读者我要写书评

暂无评论

Blind spot monitoring for car 4th

Blind spot monitoring for car

引用

4th Annual International Conference on Data science, Machine Learning and Blockchain technology, AICDMB 2023

作者： Ranjan, Aditya Pandey, Ravi Shankar Department of Computer Science and Engineering Birla Institute of Technology Patna Campus India Mesra India

ISBN: (纸本)9781032426853

Blind spot of a car is an area around the vehicle that cannot be seen while looking either forward or through side or rear view mirror. This paper introduces blind spot monitoring for vehicles using vehicle mounted cameras in order to reduce traffic accidents. We firstly describe how intelligent surveillance can be used to detect vehicle blind spots by using multiple cameras. We then describe the importance of blind spot detection including technical background. This paper provides an algorithm for vehicle detection in blind spot using Mean shift algorithm based on machine learning. In this approach, a target window is defined in an initial frame for a moving target in a video, and after that, the tracked object is separated from the back ground by processing the data within that window. After that alert message will be displayed on the screen. © 2024 The Author(s).

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Unlocking the Viability of Blockchain Adoption for Healthcare: A Feasibility Study 15

Unlocking the Viability of Blockchain Adoption for Healthcar...

引用

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

作者： Gupta, Shreya Mishra, Shreya Bajpai, Shubhranshi Yadav, Shreya Verma, Rajat Pranveer Singh Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Kanpur India

ISBN: (纸本)9798350370249

Blockchain technology holds several exciting features such as security, decentralization, data integrity, access control, consent management, etc. The healthcare industry can reach its peak with the emergence of blockchain technology in terms of an efficient Electronic Health Record (EHR) Management System. This research paper explores the feasibility of implementing blockchain to improve the existing healthcare record management system and enable better data security, interoperability, data integrity, and patient consent management. The research thoroughly addresses issues in various articles, including data privacy, regulatory compliance, and scalability, and proposes blockchain recommendations. The paper will feature a comprehensive analysis of the prospects of decentralization, which can facilitate data exchange and improve interoperability among various systems. By thoroughly analyzing the potential advantages and vulnerabilities in the existing system, this research will provide a holistic understanding of the blockchain's contribution to bringing about a revolution in the healthcare sector. © 2024 IEEE.

关键词： Blockchain technology Electronic Health Records Feasibility Healthcare Industry Interoperability

来源：评论

学校读者我要写书评

暂无评论

Cross-Domain Collaborative Filtering: A Deep Neural Network Approach for Accurate and Diverse Recommendations 2

Cross-Domain Collaborative Filtering: A Deep Neural Network ...

引用

2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Goel, Chirag Sinha, Bam Bahadur Department of Computer Science and Engineering Indian Institute of Information Technology Jharkhand Ranchi834010 India

The rapid proliferation of data and the intricate nature of user behavior in the online realm have presented new hurdles for recommendation systems, which aim to suggest pertinent items to users. Among the notable challenges, ensuring the provision of accurate recommendations across diverse domains stands out. This research paper proposes an innovative solution to tackle this challenge by developing a cross-domain recommendation system that leverages the collaborative filtering technique to generate precise and varied recommendations spanning multiple domains. The system gathers user behavior and item attribute data from various domains and employs a collaborative filtering algorithm integrated with a deep neural network. The model makes use of a Neural Network with CReLU activation along with the embeddings of the user and the item followed by concealed layers. The output layer employs tanh activation to guarantee that recommendations fall within [-1, 1]. Adam optimizer, MSE loss, and an accuracy metric are utilised in training. This architecture captures user-item interactions effectively, resulting in precise personalised recommendations resulting an accuracy of 96.5% - 97.5%. To validate the effectiveness of the model, extensive evaluations are conducted on real-world datasets encompassing movies and books. The results demonstrate that the proposed system outperforms state-of-the-art recommendation systems in terms of accuracy, as measured by precision(89%), recall(90%), and AUC(0.74) scores. Furthermore, the system exhibits robust performance even in scenarios characterized by cold-start problems and data sparsity. © 2024 Elsevier B.V.. All rights reserved.

关键词： Collaborative filtering

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：