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检索条件"机构=Computer Science and Engineering Ajay Kumar Garg Engineering College"

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Developing an Effective Model for Skin Disease Detection: Techniques and Approaches 4

Developing an Effective Model for Skin Disease Detection: Te...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Yadav, Nikhil kumar Tiwari, Amit Gaurav Verma, Harsh kumar Saxena, Arpna Ajay Kumar Garg Engineering College Varanasi India Ajay Kumar Garg Engineering College Muzaffarpur India Ajay Kumar Garg Engineering College Meerut India Ajay Kumar Garg Engineering College Ghaziabad India Ajay Kumar Garg Engineering College Master of Computer Application Ghaziabad India

ISBN: (纸本)9798350364729

This research highlights the critical role of the skin as the body's primary defense against damage and infection. Despite its importance, the skin can be vulnerable to serious infections caused by fungi, viruses, or even dust, leading to conditions ranging from acne to eczema. Some skin diseases are highly contagious and can be spread by simple contact, underscoring the need for proper diagnosis and treatment to alleviate suffering and prevent transmission. The study focuses on developing a prototype for identifying skin diseases using convolutional neural networks (CNNs), a choice based on their effectiveness in image processing tasks. This research uses CNNs to classify specific skin conditions, including hand dermatitis, hand eczema, subacute eczema, lichen simplex, stasis dermatitis, and ulcers are all different skin conditions.. The methodology integrates image processing techniques with machine learning and uses the processed images to train a CNN model. The training data consists of five classes of skin conditions from the Dermnet dataset, which includes 19600 images. The prototype achieved an accuracy of 92%, highlighting the system's potential. Research suggests that with further improvements and a larger data set, the system could significantly improve early detection and treatment of skin ailments representing a substantial advance in dermatology care. © 2024 IEEE.

关键词： Dermatitis

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Enhancing Tourism Experiences and Preserving Cultural Heritage with AR and VR 2

Enhancing Tourism Experiences and Preserving Cultural Herita...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Singh, Pancham Pahuja, Neeti Kansal, Mrignainy Gurung, Siddhant Shukla, Utkarsh Gupta, Sandeep Information Technology Ajay Kumar Garg Engineering College Ghaziabad India Ajay Kumar Garg Engineering College Computer Science and Engineering Ghaziabad India Ajay Kumar Garg Engineering College Ghaziabad India Ajay Kumar Garg Engineering College Csit Ghaziabad India

ISBN: (纸本)9798350371055

The objective of this research is to understand how virtual reality (VR), augmented reality (AR), and mixed reality (MR) are transforming the travel and tourism sectors as well as preserving cultural heritage. We are living in a digital interaction world where new immersive experiences have been induced by the interplay between technological breakthroughs, societal needs, and commercial imperatives. Given that tourism is about cultural heritage sites worldwide, this study examines the current challenges associated with their conservation within the globalization of culture. The objective is to understand how AR and VR technology can change the way people think about tourism and protect the world's cultural heritage. With this aim in mind, the paper explores different applications of AR and VR technologies while focusing on how these can offer contemporary tourists immersive and educational experiences. The authors suggest that the advantages of accessibility should be thoroughly examined;virtual visits could be used to bypass logistical, financial, or physical barriers;and the implications of such technologies for digital preservation will also be considered under this approach. It was found out that AR and VR serve as effective means of access, enabling a larger number of people from around the world to reach cultural heritage sites. Besides, it is through these technologies that significant changes in the field of preservation can be achieved, ensuring the survival of cultural assets for future generations. Lastly, this research paper will be helpful to researchers within academic circles as well as industry practitioners and policymakers who want to know how AR/VR technology is changing the travel industry or contributing to cultural heritage protection efforts. Essential for unlocking the potential of emerging digital channels fully is the need to appreciate such intricate linkages in our rapidly changing digital world. © 2024 IEEE.

关键词： Augmented Reality Case Studies Cultural Heritage Cultural Preservation Enhanced Learning Future Trends Tourism Virtual Reality Virtual Tours

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Employing Vision Transformer for Monocular Depth Estimation 2

Employing Vision Transformer for Monocular Depth Estimation

引用

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Chaudhary, Anubhav Tripathi, Dev Brat Mishra, Harsh Pathak, Prasoon Dixit, Ashish Department of Computer Science and Engineering Ajay Kumar Garg Engineering College Ghaziabad India

ISBN: (纸本)9798331530389

Monocular depth estimation (MDE) is an important task in computer vision, it enables a range of applications like robotic navigation, augmented reality and also used in surgical guidance. This paper shows the use of ViTs for MDE and focuses on the Depth Anything V2(DA-V2) model. DAV2 model leverages a teacher-student training approach and uses the synthetic and unlabeled real images which are designed to enhance the accuracy of depth estimation. DA-V2 is fine-tuned on EndoSLAM dataset and contains challenging visual scenes from endoscopic images of the stomach, colon and small intestine to check the adaptability of the model to medical depth estimation. Our experiment shows that the fine-tuned DA-V2 outperforms all the conventional models like Endo-SfMLearner and achieves reductions in root mean squared error(RMSE) and absolute relative error, across all anatomical datasets. DA-V2 achieves the RMSE values 1.245, 1.028, and 2.021 for the stomach, colon, and intestine datasets, respectively as compared to the SfMLearner's 6.387, 6.657, and 14.787. The findings show that ViTs are capable of achieving higher accuracy and generalization in monocular depth estimation tasks. This study highlights the effectiveness of DA-V2 and Vision Transformers in Monocular Depth Estimation and opens up possibilities for further model optimization. © 2025 IEEE.

关键词： Convolutional neural networks

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Bi-Directional Gravity-Oriented Search Optimization Protocol for Wireless Sensor Networks 11

Bi-Directional Gravity-Oriented Search Optimization Protocol...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Pathak, Nishant kumar Shukla, Pushkal kumar Yadav, Sandeep Ajay Kumar Garg Engineering College Computer Science Engineering Ghaziabad India

ISBN: (纸本)9798350350357

In the current intellectual milieu, the central focus is directed towards the scientific domain of the IoT, fortified by the framework of wireless sensor networks. A WSN encompasses an assembly of sensor nodes engaged in intercommunication, aggregating environmental data, sending it to a server or base station to facilitate judicious decision-making. In light of their constrained battery longevity and untimely exhaustion, demanding subsequent redeployment, these sensor nodes pose intricate challenges. Recent scholarly pursuits have utilized a clustering approach in order to improve overarching lifespan of network. Utilizing cluster heads facilitates the communication of information from nodes to the central head waiter. Notably absent in current clustering techniques is the optimal methodology for forwarding data from sensors to the server and selecting the most suitable cluster heads. This paper introduces an innovative approach for WSN in the situation of IoT applications, employing Mobile Agents (MA) to assembledata from nodes. The methodology is grounded in the Two-Fold Gravitational Search Algorithm (GSA). In this process, the Mobile Agent's route for congregation facts from feeler nodes undergoes optimization using GSA subsequent to its efficient selection of cluster heads. The optimization criteria encompass variables like nodes' residual energy and the associated communication cost in relation to the base station (BS). In the evaluation of network longevity and energy efficiency, the proposed methodology has been juxtaposed against alternative clustering protocols. Furthermore, the success rate and energy consumption associated with task execution in the MA's itinerary planning, based on the GSA, have been scrutinized in comparison to alternative itinerary planning techniques. Comparative analysis reveals that, in contrast to alternative approaches, the suggested protocol exhibits enhanced association immovability, abridged the energy consumption, and a heig

关键词： Energy utilization

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Empowering patients: Evaluating user experience with the MED-LIST platform 4th

Empowering patients: Evaluating user experience with the MED...

引用

4th International Conference on Computational Methods in science and Technology, ICCMST 2024

作者： Agarwal, Paras Choudhary, Vishal Agarwal, Swati Tyagi, Shivika Chaurasiya, Nitish Department of Computer Science and Engineering Ajay Kumar Garg Engineering College Ghaziabad India

ISBN: (纸本)9781032911571

In today’s fast-paced world, people have hectic lives. Almost everyone faces the challenge of taking their medicines on time, enduring lengthy waits for lab reports, people face challenges in managing their medical records, misplacing their medical prescriptions, navigating cumbersome appointment booking systems in the clinics, etc. This paper introduces a mobile and a web application designed to provide a complete healthcare system and resolve all the mentioned problems and many more. It will help people to connect to their respective healthcare provider and provide a notification system for medication reminders, streamlined appointment booking with integrated payment functionality, instant lab reports on the phone, disease prediction by symptoms, medicines history and reports history, an intelligent queue management system that predicts appointment times bases on a regression ML model with 85% accuracy, etc. © 2025 the Author(s).

关键词： Reservation systems

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Transforming Cardiovascular Disease Management through Advanced AI and ML-Driven Predictive Modeling and Data Visualization 1

Transforming Cardiovascular Disease Management through Advan...

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1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Gupta, Kritika Shalini Rajawat, Parth Srivastava, Anmol Dixit, Ashish Ajay Kumar Garg Engineering College Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798350367720

This groundbreaking paper, driven by AI and ML, seeks to revolutionize heart disease management globally through data visualization and predictive modeling. Given the persistent prevalence of cardiac disease, proactive measures are imperative, with early diagnosis pivotal for effective intervention. Employing advanced AI and ML techniques, our primary goal is to glean invaluable insights from extensive heart health datasets, utilizing sophisticated data visualization tools to enhance comprehension. In contrast to the current landscape of the medical field, which is abundant in data but often lacks robust analytical tools capable of discerning intricate patterns and trends, this research embarks on a journey into the realm of state-of-the-art discovery techniques housed within databases. The primary emphasis is directed towards the prediction of heart diseases, utilizing datasets traditionally confined to the realms of medical studies. A multitude of trials have been conducted, rigorously evaluating the efficacy of various predictive data mining methodologies on identical datasets. The findings underscore the superiority of decision trees over alternative techniques. While Bayesian classification occasionally demonstrates comparable accuracy to decision trees, methodologies such as KNN, neural networks, and classification generally exhibit inferior performance metrics. A significant discovery reveals that employing genetic methods to refine real data enhances the accuracy of both decision trees and Bayesian classification, resulting in remarkable outcomes conducive to heart disease prediction. The utilization of Pyplot, an indispensable tool within the matplotlib module, is vital for generating a diverse array of plots and graphs, spanning charts, histograms, scatter plots, and 3D charts. Key functionalities such as standardscaler(), expression distribution, and confusion matrix bolster the model's resilience. As this project reaches its apex, a comprehensive plan em

关键词： Decision trees

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High Degree Dependency Study of Ensemble Models in Credit Card Fraud Analysis 2

High Degree Dependency Study of Ensemble Models in Credit Ca...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Rani, Shalini Tiwari, Mayank Tyagi, Shiva Department of Computer Science and Engineering Ajay Kumar Garg Engineering College Ghaziabad India

ISBN: (纸本)9798331530389

Credit card fraud detection is an increasingly critical issue due to the growth of digital transactions and the sophistication of fraudulent activities. This study proposes a hybrid framework combining Graph Neural Networks (GNNs), ensemble methods (e.g., XGBoost, Random Forest), and polynomial feature engineering to address key challenges, including class imbalance, non-linear data relationships, and real-time applicability. The system achieved a detection accuracy of 96.7%, precision of 96.9%, recall of 96.4%, and a false-negative rate of 3.6% on benchmark datasets. These improvements are attributed to the integration of advanced sampling techniques, polynomial feature transformations, and the hybrid architecture. The findings demonstrate the effectiveness of the proposed approach in enhancing fraud detection systems and provide a scalable solution for real-world applications. © 2025 IEEE.

关键词： Graph neural networks

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Optimisation Techniques in Investment Risk Management :Scipy, SLSQP and Modern Portfolio Theory 3

Optimisation Techniques in Investment Risk Management :Scipy...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： garg, Aayushi Singh, Aditya Pratap Saraswat, Anushka kumar, Avnish Taluja, Anuradha Ajay Kumar Garg Engineering College Department of Computer Science Ghaziabad India Ajay Kumar Garg Engineering College Department of Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798331523893

Organizations achieve successful investment risk management by achieving optimal risk exposures and return objectives at the same time. The research examines optimization methodologies through its comparison of SciPy's optimization suite to SLSQP while incorporating Modern Portfolio theory. This research analyzes historical financial data to examine both risk-adjusted return metrics along with computational efficiency metrics. The research study provides detailed mathematical definitions about optimization procedures and performs quantitative assessments on data output and suggests future work that integrates machine learning with economic domains. The research demonstrates that these optimization approaches present critical methods to achieve maximum portfolio diversity. © 2025 IEEE.

关键词： Risk management

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Integration of computer Vision Systems in Robotics and Industry 4.0 2

Integration of Computer Vision Systems in Robotics and Indus...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Vikas Prasad, Rajesh Upadhaya, Santosh kumar kumar, Amit Ajay Kumar Garg Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350368109

computer vision is the field that focuses on automating and combining various processes and representations used for visual perception. The subject encompasses numerous approaches that provide individual use, such as image processing. Image processing is converting, transforming and transferring an image. This method is the statistical categorization of patterns based on applying statistical decision theory. computer vision systems are deployed in various environments, from the shop floor and hospital suite to Mars and surgical suits. Incorporating computer vision in manufacturing is a groundbreaking step towards elevating Industry 4.0 by enhancing efficiency, accuracy and connectivity. This is driven by the compelling benefits realized when computer vision can be used in a factory to create a safe environment for all stakeholders and operators, affording machines with visual perception and enabling them to process and act on the high-richness of environmental data given input by a camera. computer vision integrated into manufacturing is a drastic step towards more intelligent, efficient and connected production methods as part of Industry 4.0. This paper discusses different features of the Industrial Revolution, the role of computer vision in Industrial Revolution 4.0, and how computer vision affected the Industrial Revolution in future industry development. As computer vision debuts firsthand in commercial use in manufacturing, so is the industry about to explode with unprecedented creativity and productivity. © 2024 IEEE.

关键词： computer integrated manufacturing

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Exploring the Cloud and Fog: Addressing Security Risks in AI Applications 2

Exploring the Cloud and Fog: Addressing Security Risks in AI...

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2nd IEEE International Conference on Advancements and Key Challenges in Green Energy and Computing, AKGEC 2024

作者： Jain, Jaishree Kaur, Inderjeet Ajay Kumar Garg Engineering College Department of Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798350390179

There are various security risks with cloud- or fog-based machine learning services. Because machine learning applications rely on these services, it is imperative to secure the underlying cloud or fog services to prevent serious disruptions to the applications. We distinguish based on whether Artificial Intelligence applications are employed in a fog computing network or the cloud because the needs for these applications can also vary. This consequently gives rise to various threats or avenues for attack. Security responsibilities for cloud platforms can be split up amongst several parties. Even though fog computing networks have fewer responsibilities, we still need to safeguard services from physical access to the devices at the network's edge because they have been moved there. Lastly, we go into specific information security requirements for AI-related applications. © 2024 IEEE.

关键词： Cloud security

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