检索结果-内蒙古大学图书馆

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Ferdous, Samira Raisha Ahasan Rifat, Md Robayet Ayan, Muntasir Jahid Rahman, Raiyan Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

Ocular Toxoplasmosis (OT) is a very well-known eye inflammation that is occurred from a parasite named Toxoplasma gondii (T. gondii) that can lead to several vision problems. Diagnosis traditionally involves clinical examinations and imaging, which can be complex and expensive, requiring specialized expertise. Recently, the interest of using the domain of artificial intelligence (AI) for diagnosing various eye diseases by analyzing fundus images has been increasing. To utilize this field, in this paper, a pre-trained model named VGG16 is built using deep learning (DL) algorithms. Basically, this is trying to use Artificial Neural Network (ANN) and Convolutional Neural(CNN) to classify the fundus images that have three categorical forms of OT. The dataset was collected with 355 images, and after augmentation, the data increased to around 700 images. Augmentation is done after rotating, flipping, shifting, shearing, and zooming. Data is also preprocessed to make the visions clear for the models to predict more accurately. Later, the performance of this proposed model is measured by some evaluating factors, such as the F1-score, precision, recall, loss, accuracy, and confusion matrix. In terms of overall performance among ANN and CNN models, ANN performed better with an accuracy of 98%, whereas to get acceptable accuracy, the CNN model required changing the images to grayscale, resulting in 95% accuracy. © 2023 IEEE.

关键词： ANN Classification CNN Deep Learning Ocular Toxoplasmosis Toxoplasma gondii VGG16

来源：评论

学校读者我要写书评

暂无评论

Shoulder and Wrist Rehabilitation: A Biofeedback Simulation using IoT 7

Shoulder and Wrist Rehabilitation: A Biofeedback Simulation ...

引用

7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Sridevi, R. Sriram, S.S. Logeshsanjay, R. Manikandan, N. Venugopal, B. Department of Computer Science and Engineering Tiruchirappalli India

ISBN: (纸本)9798350397284

With developments in surgical approaches and greater knowledge of shoulder and wrist breakdown healing, it was necessary to establish reasonable progress after the operation. During recovery, there has to be an ongoing interaction with the medical staff. Pain and edema must be treated immediately, to ensure the complete recovery of patients' motion range. The therapeutic framework allows for innovative stress treatment by increasing motion range and progression between idle, dynamic assistance, and strong motions. Since time limitations truly aren't applied for growth, it is vital neither to exert enormous strain upon that shoulder and wrist for a period of twelve weeks to enable for optimal tendon-to-bone rehabilitation. When workouts progress, muscular stimulation was triggered, governed by adequate workouts which leads to rapid and consistent recovery. This system employs a micro controller as well as EMG and accelerometer sensors to detect muscle movement as well as hand position and angle while performing movements during the rehabilitation and recovery phase. This work is capable of providing muscle rehabilitation, particularly when the micro controller is used. As a result, the proposed system able to predict how quickly the patient will recover from the shoulder and wrist problems, and the current muscle activity details are presented using the Cayenne app powered by the IOT (ESP8266-12E) NODE MCU and Cayenne server. © 2023 IEEE.

关键词： Accelerometers

来源：评论

学校读者我要写书评

暂无评论

Heart Disease Diagnosis Using Machine Learning Classifiers 13th

Heart Disease Diagnosis Using Machine Learning Classifiers

引用

13th International Advanced Computing Conference, IACC 2023

作者： Singh, Pushpendra Tyagi, Chandra Shekher Sharma, Davesh Kumar Singh, Mahesh Kumar Choudhary, Pushpa Singh, Arun Kumar Department of Computer Science and Engineering SRMIST Delhi-NCR Campus Modinagar UP Ghaziabad India Department of Computer Science and Engineering Dronacharya Group of Institutions UP Greater Noida India School of Computer Science and Engineering Galgotias University UP Greater Noida India Computer Science and Engineering Greater Noida Institute of Technology UP Greater Noida India

ISBN: (纸本)9783031567025

The term "heart or cardiovascular disease" is frequently used to refer to a variety of heart-related issues. It is one of the illnesses with the highest mortality rate. Its fatality rate results in nearly 17 million deaths worldwide. Given the daily increase in heart disease cases, predicting any disease early is critical and concerning. Early detection of heart disease is a difficult task that must be accomplished carefully and effectively by gathering precise information about the patient who is at risk for heart disease. To predict whether a person has cardiac disease, there are numerous AI-based (Machine/Deep learning) Models available considering medical characteristics (features) of heart disease. By comparing and contrasting several machine learning classifiers, this paper proposed a heart disease prediction system. This system will aid in identifying and predicting whether the patient is likely to have or be diagnosed with heart disease based on his or her current medical state. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing wildlife protection: a novel approach combining deep learning and night-time surveillance

引用

Multimedia Tools and Applications 2024年 1-35页

作者： Madhasu, Nithya Pande, Sagar Dhanraj VIT-AP University Andhra Pradesh India Department of Computer Science and Engineering School of Engineering and Technology Pimpri Chinchwad University Maharashtra Pune India

The increasing instances of animals encroaching on human settlements, as well as the illicit trafficking of wildlife, have prompted immediate actions to protect the natural heritage. In addition to this, the difficulties of night-time animal surveillance are also being faced. This paper highlights the urgent necessity for comprehensive animal welfare monitoring and effective anti-illegal trafficking prevention. The expensive cost of installing night vision cameras heightens the necessity of locating an affordable and effective solution. To overcome these issues, a unique strategy, combining colorization utilizing Customised Conditional GAN (Generative Adversarial Net) for night-time applications and YOLO-CNAS (You Only Look Once-Customised Neural Architecture Search) classification for intelligent wildlife detection is proposed. Colorization during the night enables the discovery of critical nocturnal behaviors, encouraging a greater knowledge and relationship with nature. Using these powerful deep learning algorithms helps to recognize the wildlife throughout both daylight and night-time hours, as well as smugglers trespassing into the forest. The suggested method obtains an amazing testing accuracy rate that has improved from 55.73% to 72.54% and then finally to 94.67%, demonstrating the revolutionary approach's potential for animal protection. The extensive dataset used for training and assessment was meticulously sourced from various websites including iNaturalist, Unsplash, and Pexels. These platforms provided a rich array of diverse images. During the pressing need to protect the nation's irreplaceable heritage, the intelligent model provides a ray of hope. Conservationists and policymakers may work together to safeguard the natural heritage by enabling effective wildlife surveillance and maintaining a happy coexistence between humans and animals for future generations. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of S

关键词： Animals

来源：评论

学校读者我要写书评

暂无评论

SOTA: Stochastic On-Time Arrival Path Prediction and Dynamic Programming for Criticality Aware Mobile Healthcare System 17

SOTA: Stochastic On-Time Arrival Path Prediction and Dynamic...

引用

17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Singh, Himanshu Singh, Moirangthem Biken Patel, Akash Pratap, Ajay Department of Computer Science and Engineering Varanasi India

ISBN: (纸本)9798350307672

In an emergency healthcare situation, the time delay between injury and treatment is crucial for patient survival. Real-time processing of ambulance data can significantly reduce diagnosis and pre-treatment delays, resulting in faster recovery. Moreover, to achieve timely treatment, reliable and efficient paths should be followed by ambulances to reach hospitals faster. To tackle these phenomena, we utilize Stochastic On-Time Arrival (SOTA) based reliable path prediction. However, accessing real-time patient data from ambulances moving along Road Side Units (RSUs) on a reliable path poses several research challenges. Thus, this paper introduces an RSU allocation scheme founded on Dynamic Programming (DP), which takes into account latency, migration, and energy consumption as the goal of minimizing average total cost. Evaluation and prototype results confirm our hypothesis, showing marked improvement as compared to other state-of-the-art techniques on real-world datasets. © 2023 IEEE.

关键词： Dynamic programming

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Image Enhancement Algorithms for Abdomen CT Images 2

A Comparative Study of Image Enhancement Algorithms for Abdo...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Kaur, Harinder Kaur, Navjot Neeru, Nirvair Punjabi University Patiala Department of Computer Science and Engineering Patiala India

ISBN: (纸本)9798350360523

Image enhancement techniques play a vital role in improving the visual quality and diagnostic value of Computed Tomography (CT) images. As medical imaging continues to be a cornerstone of diagnosis and treatment planning, advancements in image enhancement algorithms have become essential to aid medical professionals in accurately interpreting CT scans. This research paper presents a comprehensive review and comparative analysis of various image enhancement techniques applied to medical images, with a focus on abdomen CT imaging. The study categorizes these algorithms into histogram-based, transformation-based, and deep learning-based methods, assessing their respective strengths and limitations. The research employs a meticulous comparative analysis, considering metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Average Mean Brightness Error (AMBE), Entropy, and Structural Similarity Index (SSIM) to evaluate the performance of these techniques. We conclude with the implications of the study's results, paving the way for informed decision-making when selecting enhancement techniques. © 2024 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Smart Lock Security System 2

Smart Lock Security System

引用

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

作者： Ravikumar, Pushpa Arpitha, C.N. Hemanth, N.G. Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (纸本)9798350383867

With the percentage of single-parent households rising quickly, criminal vulnerability is becoming more of a social issue The main issue is often worry over stranger visiting, especially in the case of single female families. This project focuses on the design strategy for an embedded real-time surveillance system based on a Raspberry Pi for the purpose of detecting intruders. Surveillance technology is reinforced to provide vital security for our daily lives, along with related control and alert functions. Our creative integration of cameras and motion detectors into a web application is the foundation of the suggested security system. Remote sensing cameras and motion detectors are managed and operated by Raspberry Pi. The goal of this research is to create a system that can quickly identify outsiders and respond by taking pictures and sending them to a wireless module that is based on the owner. If owner wish to add the other members to home, then he need to save the person photo in database. © 2024 IEEE.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Person Re-Identification with CNN ResNet Spatial–Temporal Stream 6th

Person Re-Identification with CNN ResNet Spatial–Temporal S...

引用

6th International Conference on Intelligent Communication, Control and Devices, ICICCD 2024

作者： Sharma, Suchi Diwakar, Manoj Gangodkar, Durgaprasad Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (纸本)9789819783281

Identifying individuals from many cameras that correspond to a given query is the goal of video-based re-identification of people (reID). Video-based person re-identification makes considerable use of the temporal attention mechanism. This challenge is significantly more difficult than image-based person reID because of the spatial and temporal distractions present in person videos, which include backdrop noise and partial closures over frames, respectively. We see that spatial distracting factors always appear in a particular place, while temporal distracting factors show different patterns, such as partial closures in the initial few frames. These patterns provide helpful cues about which frames or temporal attentions to pay attention to first. Therefore, this study works with ResNet101 as the backbone network while using spatial–temporal stream to provide an improved person re-identification method using YOLOv5 which effectively extracts features from the input source and provides a lightweight model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： CNN DG mAP PCB ReID YOLOv5

来源：评论

学校读者我要写书评

暂无评论

A comprehensive analysis of threat vectors in software-defined networking

引用

Multimedia Tools and Applications 2024年第39期83卷 86791-86832页

作者： Dahiya, Seema Sehrawat, Harkesh Kharb, Seema Siwach, Vikas University Institute of Engineering and Technology Maharshi Dayanand University Rohtak Rohtak India Department of Computer Science and Engineering SRM University Sonepat Sonipat India

In recent years, cyber-attacks have become more frequent and advanced, targeting critical infrastructure, businesses, homes, and government agencies. Detecting and preventing these attacks at the earliest stage possible is crucial to avoid serious harm, including data breaches. Researchers and experts in cybersecurity are looking to Software-Defined Networking (SDN) technologies as a solution to enhance real-time defense against cyber-attacks. SDN revolutionizes traditional networking by offering unprecedented flexibility and control over network resources, making it possible to adapt quickly to emerging threats. SDN provides logically centralized network control by separating the control plane from the data plane. This enables network programming and can block network activity when malicious movement is spotted. This paper presents a comprehensive analysis of threat vectors in SDN. It examines the various ways in which SDN networks are vulnerable to cyber-attacks, including network infrastructure, application layer, and SDN controller. The paper also evaluates the effectiveness of existing security measures and proposes future research directions to enhance SDN security. Overall, the paper highlights the potential of SDN as a powerful tool in the fight against cybercrime and emphasizes the importance of continued research and development to improve SDN security. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Improving Face Recognition for Smart Home Security: A Study of Resnet, Siamese Networks, and Attention Mechanisms

Improving Face Recognition for Smart Home Security: A Study ...

引用

2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Sood, Hemaang Nikhil, B.V.S. Dengla, Palak Saeed, Sanya Nagabhushan, S.V. Bms Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331538538

This study presents a smart doorbell system designed to improve home security through advanced deep learning techniques. At its core, the system utilizes the YOLOv5 (You Only Look Once) algorithm for real-time face detection, ensuring accurate and efficient visitor identification. To further strengthen security, the system employs multifactor authentication (MFA), integrating face recognition alongside speech recognition and or/a manual keypad. The study evaluates three neural network architectures for face recognition-ResNet with cosine similarity, a Siamese network with CNN, and an attention-enhanced Siamese network-to determine the most effective model for secure and reliable authentication. Performance comparisons highlight progressive improvements in accuracy and robustness,. Additionally, a convenient interface enables seamless remote monitoring and control, enhancing both security and convenience. By addressing key limitations of existing smart security systems, this research provides insight into improving intelligent home access control. © 2025 IEEE.

关键词： Authentication

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：