检索结果-内蒙古大学图书馆

3rd International Conference on Artificial Intelligence and Signal Processing, AISP 2023

作者： Srivastava, Kushagra Pandey, Trilok Nath Roy, Debaraj Sahoo, Sambit Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350320749

This paper discusses the clinical chatbot which could examine the contamination and deliver essential insights regarding the contamination previous to counseling a specialist. To lower the healthcare charges and similarly increase openness to clinical facts the clinical chatbot is constructed. Certain chatbots pass approximately as clinical reference books, which facilitates the affected person to discover approximately their contamination and assists with running on their fitness. The person can accomplish the real gain of a chatbot simply while it is able to examine all forms of infections and deliver essential data. In later sections of the paper, a doctor appointment system software is also discussed that is integrated with the chatbot so that the specialist which is recommended by medical chatbot can be easily visited at the mutually agreed time of both specialist and patient. Such an appointment system has its own advantages like it reduces the waiting time of the patient, patients can choose the appointment time in keeping with their desire additionally to be had and booked slots are proven in powerful graphical person interface. © 2023 IEEE.

关键词： Health care

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Anti-Image Manipulation Techniques: Advancements and Challenges 2

A Comprehensive Analysis of Anti-Image Manipulation Techniqu...

引用

2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Ilavendhan, A. Vignesh, N. School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350340235

Every individual relies on technology either directly or indirectly. Living in an Information Era means that even one's birthday is known to others who haven’t been se en for years, via social media. This is possible because of the data that the social media extracts from the user and keeping it securely in their database as information. Even with the assurance given by the media companies about the information they store, many of us still refuse to share the personal data online because of the factors like Data Breaches, Data phishing, etc. Even if personal data access is granted, the images posted on social media undergo unsightly alterations through various AI modification techniques employed by certain individuals. With these image alterations ranging from subtle enhancements to sophisticated forgeries, the need for robust solutions to detect and mitigate these manipulations has become very crucial. This research study is based on a novel approach to traverse through various approaches in preventing images getting altered through AI. © 2023 IEEE.

关键词： Data Breaches Data phishing Database Robust Sophisticated

来源：评论

学校读者我要写书评

暂无评论

Leveraging Ensemble Voting and Fine-Tuning Strategies in Pre-Trained Transformers to Detect Prejudicial Tweets and Hurtful Humour

Leveraging Ensemble Voting and Fine-Tuning Strategies in Pre...

引用

2023 Iberian Languages Evaluation Forum, IberLEF 2023

作者： Kaoshik, Jay Kather, Sharmila Banu School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India

The contents of this paper describe our system which was submitted to the HUrtful HUmour Detection (HUHU) task at IberLEF 2023. The proposed system achieved a F1 score of 0.781 for Task 1 (binary classification) using an ensemble of pre-trained transformers which included DistilBERT Cased, XLM-RoBERTa Spanish, RoBERTuito Cased, mBERT Cased and BERT Cased. A Macro F1 score of 0.739 was obtained for Task 2A (multi-label classification) using ensemble voting from mBERT Cased, BETO Cased, BETO Uncased, DistilBERT Spanish and RoBERTa. For the final Task 2B (regression), our proposed system achieved a RMSE score of 0.938 when the pre-trained transformers were fine-tuned with a fully connected layer (regression head) over the pre-final layer. For the regression task, an ensemble of BETO Cased, BETO Uncased, ALBERT Spanish, DistilBERT Spanish and RoBERTuito Uncased was used. Our proposed ensemble system ranked in the Top 10 systems team-wise for Subtasks 1 and 2A without using knowledge from a high performing baseline i.e. Bloom-1b1 and without any form of data pre-processing or augmentation. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Detection and Analysis of Port Scanning and SQL Injection Vulnerabilities with correlating factors in Web Applications to Enhance secure Data Transmission

Detection and Analysis of Port Scanning and SQL Injection Vu...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Sheik Abdullah, A. Aravind Shankar, R. Mohapatra, Pratiksha School of Computer Science and Engineering Vellore Institute of Technology Chennai TamilNadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai Madhya Pradesh Singrauli India

ISBN: (纸本)9798350305708

The increasing use of web applications has led to a rise in vulnerabilities, with SQL injection being one of the most prevalent and harmful attacks. Attackers exploit flaws in how web applications handle user input to manipulate database queries and gain unauthorized access to sensitive data or perform destructive actions. This article aims to explore the working of SQL injection attacks and highlight the role of port scanning in such attacks. By understanding the causes and mechanisms behind SQL injection, we can better comprehend the importance of proper input validation and parameter handling in securing web applications. The study reveals that web applications vulnerable to SQL injection can be exploited through port scanning to identify open or closed ports, like MySQL's default port 3306. Attracting malicious SQL code into user input fields can alter database queries and potentially compromise the application's security. SQL injection remains a significant threat to web applications due to poor input validation and inadequate handling of parameters in SQL queries. Proper security measures, such as input validation and parameterization, are crucial to mitigate the risk of SQL injection attacks and enhance overall application security. © 2023 IEEE.

关键词： Data Analysis Port Scanning SQL injection attacks Vulnerabilities Web Applications Web security

来源：评论

学校读者我要写书评

暂无评论

Automated semantic segmentation and Diagnosis of Coconut Tree Infection Using Drone Imagery and Machine Learning approach for smart agriculture

Automated semantic segmentation and Diagnosis of Coconut Tre...

引用

2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Vasumathy, M. Devakanth, J. Jude Moses Anto Thirugnanam, Mythili Roselinkiruba, R. Hamsaveni, R. Nandhini, R. Kingston Engineering College Computer Science and Engineering Tamilnadu Vellore India Madanapalle Institute of Technology & Science Department ofComputer Applications Andhra Pradesh Madanapalle India Vellore Institute of Technology School of Computer Science and Engineering Tamilnadu Vellore India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Computer Science and Engineering Tamilnadu Chennai India Computer Science and Engineering Andhra Pradesh Chittoor India D.K.M College for Women Computer Science and Applications Tamilnadu Vellore632001 India

ISBN: (纸本)9798331539948

The coconut industry of our Indian nation contributes an extensive range of economy to the national GDP. About 19,247 million coconuts, or 31.45% of the world's production, were produced in India in the year 2021-2022 making it the top producer. However, the coconut farmers face major challenges from a plethora of pests and diseases of coconut trees, and yield loss, which affects the farmers economically, standing around at 10-15%. Major pests, such as Rhinoceros beetles and red palm weevils, are highly destructible, in some scenarios leading even to the mortality of crops. In most of the cases, when trees that are affected need a cure, farmers have to climb the trees to put chemicals in crowns infested with the pests, exposing the farmers to harmful chemicals and risking severe injuries or permanent disabilities. As a solution, the proposed methodology involves the collection of extensive drone imagery from coconut plantations, followed by the annotation and preprocessing of the data. This work utilizes state-of-the-art deep learning models, including Unet, convolutional neural networks (CNNs) for semantic segmentation, to differentiate coconut trees from the background and other vegetation. Subsequently, machine learning classifiers are employed to diagnose diseases by analyzing visual symptoms present in the segmented trees. The proposed approach offers significant improvements in accuracy and efficiency compared with other traditional manual methods, providing real-time insights into tree health and disease management. This system has the potential to enhance crop monitoring, optimize resource allocation, and ultimately increase agricultural productivity. © 2024 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

A dual fuzzy with hybrid deep learning architecture based on CNN with hybrid metaheuristic algorithm for effective segmentation and classification

引用

International Journal of Information technology (Singapore) 2023年第1期15卷 531-543页

作者： Nagoor, Shafeen Jinny, S. Vinila Department of Computer Science Noorul Islam Centre for Higher Education Thuckalay Kumaracoil India School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Tuberculosis (TB) is becoming a deadly disease that causes tremendous death throughout the world. Early diagnosis of TB is a crucial task that helps to prevent the disease from severity. Therefore, several types of research are being held worldwide for providing a highly effective automatic diagnosing system. Hence, the proposed model has emerged where segmentation, feature extraction, and classification are the three significant parts. In segmentation, Fuzzy Kapur’s Entropy-based Multi-Level Segmentation with Quantum Bat Optimization Algorithm (QBO_KMLBS) is utilized. Secondly, a Deep Inception with Fuzzy based Support Vector Machine with Sine Cosine Optimization algorithm i.e., named SCHHO-IVFSVM is utilized for feature extraction and classification. In this work, the fuzzy logic has been applied to both the segmentation and classification stages in order to improve the performance model of the TB diagnosis. The implementation is done in the MATLAB 2020 platform and the performance is evaluated in terms of performance matrices with four different categories such as single, overlapped, single and overlapped, and overall. These categorizations are evaluated with different datasets and techniques. Finally, the proposed method has shown 96.89% accuracy for the conventional sputum smear microscopy database (CSM_DS) dataset. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management.

关键词： Fuzzy InceptionV4 Kapur’s entropy Multilevel segmentation Quantum bat optimization Support vector machine

来源：评论

学校读者我要写书评

暂无评论

Weighted Average Ensembled Probability Pipeline of Pre-trained CNN Models for Hand Gesture Classification 15

Weighted Average Ensembled Probability Pipeline of Pre-train...

引用

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

作者： Gunti, Rahul Rohan Reddy, B. Swathi, Gunti Sharath Kumar Reddy, G. Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai601103 India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350370249

The automatic detection of sign language from hand gesture images is fundamental for effective human-computer interaction, especially for individuals with hearing and speech disorders. Achieving accurate detection and classification of sign language gestures is paramount. However, accurately recognizing these gestures frequently presents challenges due to dull backgrounds, variations in gesture orientation, and fluctuations in lighting conditions. Previous approaches tried to overcome these challenges but still the model performance lacks recognition accuracy and visual quality. To address this need for accuracy, we proposed a Weighted Average Ensembled Probability Pipeline composed of EfficientNetB7, ResNet-50, and Xception models. Leveraging the Extensive Hand Gesture Recognition Database (HGRD), comprising 20,000 images, our individual models achieved notable accuracies: 96.498 % for EfficientNetB7, 93.2 % for ResNet-50, and 90.175 % for Xception. Through ensemble learning, we integrate these models to attain an impressive overall accuracy of 98.95 %. This research contributes to robust gesture recognition system and underscores the significance of ensemble techniques in enhancing performance for Gesture recognition systems. © 2024 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Predicting Severity Levels of Parkinson’s Disease from Telemonitoring Voice Data 7th

Predicting Severity Levels of Parkinson’s Disease from Tele...

引用

7th International Conference on Inventive Systems and Control, ICISC 2023

作者： Vats, Aryan Blouria, Aryan Sasikala, R. Vellore Institute of Technology Tamil Nadu Vellore632014 India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India

ISBN: (纸本)9789819916238

Parkinson’s disease is an age-related degenerative brain disorder that affects the nervous system causing symptoms such as tremors, stiffness and slowing of movement that begin gradually and worsen over time. As severity increases, problems such as mental and behavioral changes, memory issues, depression and fatigue arise. As such, to be able to successfully diagnose and cure patients of Parkinson’s, we need an accurate and reliable means to identify the severity of the disease. This paper proposes a method of severity prediction using neural networks, with the adequate number of severity levels backed by statistical proofs. This paper focuses on obtaining an accurate number of clusters using the telemonitoring voice dataset of patients, and through our experiments, we arrive at four severity levels. In the proposed approach, emphasis was given to consider more parameters for prediction and the exactness of the values obtained by our strategy to be better when contrasted with the precision acquired in past research. The system proposed can classify Parkinson patients into more severity levels than just ‘severe’ and ‘non-severe’ and consequently can help clinical professionals in medical care diagnose Parkinson illness. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Efficient Authentication System Using Wavelet Embeddings of Otoacoustic Emission Signals

引用

computer Systems science & engineering 2023年第5期45卷 1851-1867页

作者： V.Harshini T.Dhanwin A.Shahina N.Safiyyah A.Nayeemulla Khan Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringChennai603110India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

Biometrics,which has become integrated with our daily lives,could fall prey to falsification attacks,leading to security *** our paper,we use Transient Evoked Otoacoustic Emissions(TEOAE)that are generated by the human cochlea in response to an external sound stimulus,as a biometric *** are robust to falsification attacks,as the uniqueness of an individual’s inner ear cannot be *** this study,we use both the raw 1D TEOAE signals,as well as the 2D time-frequency representation of the signal using Continuous Wavelet Transform(CWT).We use 1D and 2D Convolutional Neural Networks(CNN)for the former and latter,respectively,to derive the feature *** corresponding lower-dimensional feature maps are obtained using principal component analysis,which is then used as features to build classifiers using machine learning techniques for the task of person identification.T-SNE plots of these feature maps show that they discriminate well among the *** the various architectures explored,we achieve a best-performing accuracy of 98.95%and 100%using the feature maps of the 1D-CNN and 2D-CNN,respectively,with the latter performance being an improvement over all the earlier *** performance makes the TEOAE based person identification systems deployable in real-world situations,along with the added advantage of robustness to falsification attacks.

关键词： Person identification system cochlea:transient evoked otoacoustic emission wavelet transform convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Intracranial Haemorrhage Detection Based on Deep Learning Using CT Images 2023

Intracranial Haemorrhage Detection Based on Deep Learning Us...

引用

15th International Conference on Contemporary Computing, IC3 2023

作者： Mishra, Pratyush Raj Ilavarasi, A.K. School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Computer Science and Engineering Centre for Healthcare Advancement Innovation and Research Vellore Institute of Technology Chennai India

ISBN: (纸本)9798400700224

Intracranial haemorrhage (ICH) is a medical condition that can have life-threatening consequences if it is not promptly diagnosed and treated. Diagnostic tools for medical imaging, such computed tomography (CT) scans, can help identify ICH. In this study, we investigated the application of deep learning methods to CT scan images used for ICH diagnosis. In particular, the authors made use of the Block Matching 3D (BM3D) algorithm for image pre-processing, the Densenet121 neural network design, and the Hough Transformation for image transformation. The objective was to create a model that could correctly identify and categorize ICH in CT scan pictures. The region of interest (ROI) in the CT scan pictures was then located and extracted using the Hough Transformation approach. Overall, the findings of this study show the potential of deep learning methods to support ICH diagnosis from CT scan pictures. The suggested approach was highly accurate and has the potential to help radiologists identify ICH. © 2023 ACM.

关键词： Diagnosis

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：