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检索条件"机构=MTech Computer Science and Engineering School of Computing Science and Engineering"

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Enhanced Diabetic Retinopathy Grading Using a Deep Hybrid Approach 15

Enhanced Diabetic Retinopathy Grading Using a Deep Hybrid Ap...

引用

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

作者： Laharesh, Gali Chandra, G.V.S. Sarath Sakthi Vikkraman, R. Kumar, S.B.S. Mani Suchithra, M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370249

In recent times there have been significant achievements in deep learning methodologies, the task of classifying retinal diseases is still challenging because of their minute pathological regions. The retina's blood vessels can be compromised by diabetic retinopathy, a complication arising from diabetes falls under the distinct category of retinal diseases. Despite many attempts with classification models such as CNN and other deep learning approaches detection encounters several challenges. These include existing deep learning models are susceptible to biases towards either local or global perspectives. These biases can impact semantic-level understanding of these representations. This work proposes a hybrid framework for Diabetic retinopathy grading. Inspired from the achievements of vision transformers in image classification and its ability to capture spatial relationships in fundus images related to Diabetic retinopathy features. Augmenting this vision transformer with traditional multiple instance learning forming a hybrid model ViT-MIL. By combining ViT's global learning capabilities with MIL's effective local feature extraction this hybrid model achieves enhanced performance. © 2024 IEEE.

关键词： Diabetic retinopathy Hybrid Multiple Instance Learning Vision Transformer

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Tweeting the Blues: Leveraging NLP and Classification Models for Depression Detection 2

Tweeting the Blues: Leveraging NLP and Classification Models...

引用

2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Chereddy, Spandana Geetha, K. Sreedevi, A.G. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9798350371314

Depression is a global mental health problem while Twitter is a valuable medium on which content indicating emotional affect is generated. Our research draws upon NLP to analyze tweets by the application of Naive Bayes, Support Vector Machines, and Logistic Regression classifiers. The first objective will be the tweets' classification into positive and negative sentiment categories with a secondary goal to explore the possibility of the detection of community characteristics including gender, age, and location. We investigate the tweet content by using NLP in an attempt to pinpoint the sensing patterns and the department that can reliably be used to detect depression. Results of the experiments proved comprehensive model accuracy with Support Vector Machines taking a better position on the matter of correctly classifying depression tweets. Especially, Support Vector Machines gave an accuracy of 85%, and values for precision, recall, and f1 were 0.89, 0.63, and 0.63, respectively. Therefore, the remaining ones for attaining higher accuracy and recall are difficult to achieve in models that are depressed but there is still the necessity for more data generation. This research thus clears the way for NLP in the diagnosis of mental health by providing vital assessment data that can be used by psychologists, researchers, health authorities, and policymakers to develop targeted intervention strategies and advancement of public health goals. © 2024 IEEE.

关键词： Support vector machines

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Smart Surveillence Drone with Navigation System 5

Smart Surveillence Drone with Navigation System

引用

5th IEEE International Conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Padmavathi, A. Vyasasreevedansh, B. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

At present, in this time of technological advancement and an urgent necessity for advanced spying abilities, the 'Smart Surveillance Drone with Navigation System' program is leading the way in redefining the field of surveillance and safeguarding. The way in which this project is leading is through the integration of the most advanced drone technology, complex navigation systems, and real-time computer vision, striving to create an independent drone model that can be identified and followed by human subjects in real-time while travelling between predetermined waypoints. The key aims of the program involve the assembling and integrating of a range of sensors, such as GPS, IMU, cameras, ultrasonic sensors, and LiDAR, alongside the production of independent navigation algorithms and computer vision technology. By combining cutting-edge technologies such as wireless communication, real-time data processing, and machine learning, the revolutionising of surveillance in several domains is being set out by this project. The adaptability and reliability of the system will be verified by rigorous field testing, while the experience will be enhanced by user feedback and training. With such advancements, the future of disaster response, agriculture, search and rescue operations, and security is promised to be innovative and efficient. This project that's set to change how we think about surveillance and security is captured by this short summary, and the way is being paved for a safer and more secure world. © 2024 IEEE.

关键词： Autonomous Surveillance Navigation System Real-time Object Detection Security Innovation Surveillance Drone

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Interactome: A Platform for Comprehensive Drug-Drug Interaction Analysis 15

Interactome: A Platform for Comprehensive Drug-Drug Interact...

引用

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

作者： Sivakumar, Amrutha Bhanot, Shreya Srinidhi, M. Aiswariya Milan, K. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350370249

Drug-drug interaction is an important aspect to be taken into consideration when administering multiple drugs to patients with severe diseases. It is important to know if the combination of the drugs causes a positive effect or an ill effect on the person's body. Thus, Interactome roots to offer a comprehensive solution to assess and find out the interactions between commonly used drugs for the treatment of different ailments such as heart diseases or diabetes and provides an understanding of how the combination of these drugs can cause side effects if not provided with enough details about the drug. Thus, it enables the user to know alternatives to using efficient drugs without any side effects by displaying graphs of the percentage of positive and negative effects and charts depicting the effects. By providing negative and positive feedback on the combination of various drugs used for heart and diabetes patients and displaying the percentage risks with the help of graphs and charts, Interactome ensures the prevention of any unnecessary attacks. Also, it saves the lives of an individual by spreading awareness about drug-drug interactions. We incorporate a Trie data structure that efficiently analyzes the input medications against a database of known interactions. It optimizes the retrieval process by organizing the drugs into a hierarchical structure. Then it ensures rapid and accurate results so that healthcare professionals and individuals receive timely and comprehensive insights into potential drug interactions. © 2024 IEEE.

关键词： charts Drug-drug interaction graphs negative effects positive effects Trie data structure

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Harnessing the Power of web3: A Blockchain Approach to Crowdfunding 15

Harnessing the Power of web3: A Blockchain Approach to Crowd...

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

作者： Savant, Richa Vivek Sunder, S. Navin Spoorthi, M. Rajagopal, Shinu M. Balakrishnan, Roshni M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350370249

Conventional crowdfunding methods frequently involve intermediaries, lack transparency, encounter regulatory challenges, and are not highly secure. Instead, a blockchain-based agreement can be formed, carried out, and enforced between members without the assistance of a third party. To achieve this, creating smart contracts, with blockchain-compatible executable code, is crucial. Additionally, cryptocurrency can be used, for which crypto wallets can securely store private keys, giving users access, control, and ownership over their digital assets while also encouraging decentralization and interoperability. Crypto wallets protect users' assets against cyber threats and unauthorized access by utilizing technologies like encryption, two-factor authentication, and multi-signature support to provide strong authentication and protection. Using a web3 platform like Thirdweb eliminates the need for an administrator by providing automated tools and infrastructure that streamline the creation, management, and deployment of decentralized applications. This study proposes the use of web3 technology to create a multi-user cross-platform blockchain-based crowdfunding DApp which employs Ethereum, smart contracts via solidity and crypto wallets for decentralized fundraising. © 2024 IEEE.

关键词： Authentication Blockchain Crowdfunding Crypto Wallets Cryptocurrency DApp Digital Assets Ethereum Private Keys Smart Contracts Solidity Thirdweb web3 Technology

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computer Vision Based Algorithms for Detecting and Classification of Activities for Fall Recognition on Real Time Video 3

Computer Vision Based Algorithms for Detecting and Classific...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Kandukuru, Tirumala Kumar Thangavel, Senthil Kumar Jeyakumar, G. Amrita Vishwa Vidyapeetham Amrita School of Computing Coimbatore Department of Computer Science and Engineering India

ISBN: (纸本)9798350372120

Falls among the elderly population present significant risks, including serious injuries and even death. Prompt detection of falls is crucial for immediate assistance and notification to relevant parties. However, current fall detection systems face challenges and privacy concerns. To address this, a new system is proposed using a Convolutional Neural Network (CNN) and optimizing Optical Flow images through preprocessing in spatial and frequency domains. The system incorporates the Viola-Jones algorithm for human face and action recognition. It is designed for detecting falls in home or room environments, covering various postures - standing, sitting, walking, and falling. Surveillance cameras in public spaces capture relevant data for training the model. The system achieves impressive accuracy and precision, highlighting its effectiveness in fall detection applications. © 2024 IEEE.

关键词： Fall detection

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Comparative Image Analysis of Chest X-RAY Image Encryption using Symmetric and Asymmetric Key Encryption Algorithms 8

Comparative Image Analysis of Chest X-RAY Image Encryption u...

引用

8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Pavani, Bhupathi Vishva Bhumika, Challagulla Sai Jagadeesh, Dumpa Venkata Sai Kavitha, C.R. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350367904

Assuring the medicinal data is very important for protecting the patient's privacy and their trust in the team. Prohibited access to confidential medicinal data gives rise to privacy breaches, healthcare scams, and improper health treatment. The technique that is suggested offers an opportunity for the encryption of chest scan images. The approach makes use of a multilayer encryption mechanism that contains a hashing layer, a digital signature layer, and the final encryption layer. The utilization of multiple algorithms for the layers mentioned above is analyzed and contrasted. For the encryption of an image, two algorithms are used which are AES and DES. For creating a digital signature, RSA and DSS are utilized. For all the three methods mentioned, RSA Key Encryption and SHA-256 hash algorithm are been frequently used. As for the evaluation metrics for the three approaches, time and space complexities are computed. The methods mentioned above prove the CIA triad which is confidentiality, Integrity, and authentication of the chest X-ray images. The most effective approach proves to be AES image encryption with RSA digital signature as it takes a short amount of time to decrypt. © 2024 IEEE.

关键词： Anonymity

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Cryptographically Secured Data Transmission Over a Network with NetCAT 1

Cryptographically Secured Data Transmission Over a Network w...

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1st IEEE International Conference on Electronics, computing, Communication and Control Technology, ICECCC 2024

作者： Rao, Subhiksha Suresh Mishra, Sahil Akhilesh, S. Kavitha, C.R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350371802

This study focuses on cryptically secure data trans-mission on a network with NetCAT and emphasizes the improvement of the Advanced Encryption Standard (AES) algorithm to improve data security. It specifically addresses file encryption using the modified AES and uses the flexibility of NetCAT utility for safe transfer. In particular, the deliberate transformation of intercepted data into incomprehensible gibberish emphasizes the robustness of modified AES against potential surveillance and unauthorized access. This document presents an improved and practical approach to improving data protection during trans-mission, especially in the context of encrypted data transmission through a network with NetCAT. Through the discussion of this specific topic, it contributes significantly to the evolving field of cryptography and emphasizes the need for accurate specifications and a clear focus on the treatment of data security challenges. © 2024 IEEE.

关键词： Cryptography

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Modeling Plant Health Monitoring Solutions for Farmers and Gardeners 8

Modeling Plant Health Monitoring Solutions for Farmers and G...

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8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Sampath, A.V.S.S. Pranav, G Meher Mahuli, Saurabh Kiran Kanapathi, V. Radha, D. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350367904

Monitoring plant health is crucial for ensuring optimal growth and preventing diseases. An accurate and reliable monitoring system plays a vital role in modern agriculture and enables farmers to make the right decisions and improve crop production. The project aims to build an understanding of how plants grow and stay healthy. The non-deterministic Finite automata (NFA) is used to represent the different health stages of the plant, like whether it is healthy or unhealthy. At first, the NFA is made with all the relevant transitions, then the limitations of this approach are discussed, and then opt for a better alternative like a Pushdown Automata (PDA), which could handle more complex situations in a better manner. Overall, the aim is to improve the understanding of plant health and help farmers and gardeners take better care of their plants. © 2024 IEEE.

关键词： Agriculture Automata Theory nondeterministic finite automaton (NFA) Plant Health Monitoring Pushdown Automaton (PDA)

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Dynamic Face Interaction: Simulating 3D Spatial Relationships with Mesa and OpenCV 15

Dynamic Face Interaction: Simulating 3D Spatial Relationship...

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

作者： Podupuganti, Ravi Charan Injeti, Hemanth Kandula, Ashish Paul Jaiswal, Rishu Inuguri, Anantha Hothri Khanna, Manju Bangalore Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering India

ISBN: (纸本)9798350370249

The dynamic face interaction model simulates real-time spatial connections by calculating distances between recognized faces and a camera by merging Mesa and OpenCV. It leverages OpenCV's Haar cascades to offer dynamic face interactions depending on proximity in 3D space through the use of FaceAgent and FaceDistanceModel classes. It is useful for social dynamics, surveillance, and human-computer interaction. It employs LBPH facial recognition and Haar cascades to precisely modify agent placements. The purpose-built dataset addresses difficulties in comprehending social dynamics and strengthens the originality of research while promoting ethical research practices. This creative method highlights the transformational potential of combining simulation and AI technologies, and it encourages researchers to carefully examine the dataset in quest of significant breakthroughs while being aware of biases. © 2024 IEEE.

关键词： Face recognition

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