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GNN-based Disease Detection and Classification in Cassava Leaf 5

GNN-based Disease Detection and Classification in Cassava Le...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Meenalochini, M. Amalroshini, A. Nandhini, K L Megha Murugan, C R Sogil Kongu Engineering College Dept. of Computer Science and Design Erode India

ISBN: (纸本)9798331518097

Cassava, a staple crop for millions of people worldwide, is highly susceptible to various leaf diseases, which can significantly reduce crop yields. Detecting and classifying these diseases at an early stage is crucial for effective disease management and crop protection. In this paper, we propose a novel approach for cassava leaf disease classification by combining Convolutional Neural Networks (CNNs) and Graph Neural Networks (GNNs). While CNNs excel at extracting local features from images, they often fail to capture complex spatial relationships between different regions of the leaf. To address this limitation, we integrate GNNs, which are well-suited for learning from irregular, structured data, such as the vein patterns and disease spread structures found in cassava leaves. By modeling the relationship between different regions of the cassava leaf as a graph G (V, E), where V represents nodes corresponding to superpixel regions of the leaf, and E represents edges capturing spatial relationships, the hybrid CNN-GNN model offers a more comprehensive and accurate classification system. The model is trained and evaluated on a dataset of cassava leaf images covering multiple disease categories, demonstrating superior performance over traditional CNN-based image classification techniques. This approach provides a scalable solution for improving the detection and management of cassava leaf diseases. © 2024 IEEE.

关键词： Convolutional neural networks

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Personality Analysis Using Graphology and Image Processing Techniques 1

Personality Analysis Using Graphology and Image Processing T...

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1st International Conference on Data, Computation and Communication, ICDCC 2024

作者： Jadon, Anshika Gutpa, Harsh Shyan, Er. Hatesh Tyagi, Aayush Raj, Tejaswi Chandigarh University Dept. of Computer Science & Engineering Mohali140413 India

ISBN: (纸本)9798331532956

This research studies the role of advanced image processing and graphology at a higher level of complexity, that is, predicting grief by interpreting handwriting. The aim of this study is to establish a reliable model, which gets a connection between the deep learning techniques and a certain set of handwriting parameters that would depict a person's mental state. This method combines the foundations of traditional graphology with the newest advancements in computer technology, such as TensorFlow and Keras, and use CNNs for feature extraction. Advanced machine learning methods including PCA, Random Forest, SVMs, and Gradient Boosting are used to improve the model's ability to classify emotional states from handwriting. The results show that the model has established discriminative capability in classification of 85% of samples with precision and recall values at 88% and 82%, respectively. This research amalgamating the traditional graphology with modern practices in psychology provides an opportunity for further enhancements in mental health evaluation through handwriting-based approaches. © 2024 IEEE.

关键词： Photointerpretation

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Text-Based Sentimental Analysis to Understand User Experience Using Machine Learning Approaches 9

Text-Based Sentimental Analysis to Understand User Experienc...

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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Gokulapriya, R. Sambandam, Rakoth Kandan Balamurugan, M. Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350397376

Data Analysis is turning into a driving force in every industry. It is a process in which data is analyzed in multiple ways to come to certain conclusions for the given situation. Sentiment analysis can be said to be a sub-section of data analysis where analysis is carried out on the emotions and opinions of the text. Social media has a plethora of sentiment data in various forms such as tweets, updates on the status, and so forth. Sentiment analysis on the huge volume of data can help in identifying the opinions of the general *** primary goal is to find the opinion of customers on the services of the Bangalore airport and to enhance the nature of these services according to the feedback provided. In this paper, we aim to measure customer opinion on services provided by Bangalore Airport through sentiment. Data is collected by a python-based scraper. The tweets are processed to determine whether they are of positive or negative opinion. These opinions are then analyzed to determine the factors which cause the negative opinions and the airport staff are alerted about the same. Various algorithms were used as part of the experimental analysis. LSTM produces more accuracy compared with existing approaches. © 2023 IEEE.

关键词： Python

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Analysis of Ensemble Machine Learning Models for Fraud Detection

Analysis of Ensemble Machine Learning Models for Fraud Detec...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Chaurasia, Siddharth Kesharwani, Satyam Sharma, Shanu Sharma, Swati Chugh, Bharti Kiet Group of Institutions Dept. of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350375237

Recent developments in electronic payment and e-commerce have led to a rise in digital fraud cases, including credit card fraud. Within the financial services industry, identifying credit card fraud is still a difficult task that can have significant effects on consumers' and financial institutions' reputations. Therefore, it is crucial to implement systems capable of detecting credit card fraud. This research utilizes the European Cardholder Data Collection to assess the efficacy of ensemble machine learning techniques in identifying credit card fraud. The European cardholder data set is subjected to a rigorous assessment and evaluation of series of machine learning models, such as Gradient Boosting, Random Forest and CAT Boost, to detect fraudulent transactions. It has been noted that the dataset is unbalanced, which may indicate that the models' performance is not very ideal. The study suggests using data sampling strategies to achieve a balanced distribution of data across various algorithms that yield optimal outcomes. The main goal is to identify the model that performs best for machine learning classification problems by comparing the performance of different models. The results of this study will support further initiatives to improve credit card transaction security and lower financial losses brought on by fraud. © 2024 IEEE.

关键词： Losses

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Voice Mate: Voice Controlled Chessboard for Visually Impaired

Voice Mate: Voice Controlled Chessboard for Visually Impaire...

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2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Abraham, Anishamol Mammen, Agnel Soyi, Ajay Jhonson, Ben Biju, Joel Amal Jyothi College of Engineering Dept. of Computer Science Kottayam India

ISBN: (纸本)9798350382693

Traditional chess can affect people with disabilities who have physical difficulty controlling the pieces, although the concept and gameplay are closely related. This paper explores the concept of voice-controlled chessboards to address this gap and encourage participation in chess. This paper presents a method for creating voice-controlled chessboards. This method introduces the structure of the circuit board, focusing on communication skills. It explains how to use stepper motors to move the chess according to commands. The paper recognises the importance of careful observation and control to ensure correct pronunciation and good chess performance. This paper discusses possible implications and areas that require further consideration. These areas include ensuring speech accuracy, maintaining reliable status monitoring of the card, and ensuring motor control. Solving these issues through development and testing is crucial to the success of voice-controlled chessboards. The paper concludes by highlighting the importance of user testing with target users (people with disabilities) to improve usability. This project has the potential to not only make chess more accessible but also stimulate the development of new technologies for a variety of recreational games. © 2024 IEEE.

关键词： Stepping motors

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Augmenting Sentiments into Chat-GPT Using FacialEmotion Recognition 10

Augmenting Sentiments into Chat-GPT Using FacialEmotion Reco...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Iyer, Aditya A. Vojjala, Saipranav Andrew, J. Manipal Institute of Technology Dept. of Computer Science and Engineering Manipal India

ISBN: (纸本)9798350384369

This research initiative addresses the task of enhancing Chat Generative Pre-trained Transformer's (ChatGPT's) conversational capabilities by integrating the comprehension and response to user emotions conveyed through facial expressions. The central challenge lies in refining the AI system's proficiency to tailor responses according to users' detected emotional states. In this pursuit, our study adopts a comprehensive approach, aiming to seamlessly incorporate emotional intelligence into AI-driven interactions. To achieve this objective, the methodology involves integrating real-time sentiment analysis based on facial expressions into the ChatGPT framework. This is carried out through the utilization of a deep convolutional neural network (DCNN) architecture, designed to recognize and interpret various emotions exhibited in facial expressions. The primary goal is to enable ChatGPT to dynamically adjust its responses, fostering a more empathetic and contextually relevant interaction with users. In terms of evaluation metrics for facial expression recog- nition, our assessment employs a confusion matrix to quantify the model's performance across different emotional categories. Additionally, a heuristic approach is implemented, wherein the sum total probability of each detected emotion is calculated over the duration the user enters the prompt. These evaluation methodologies aim to provide a comprehensive understanding of the model's accuracy and effectiveness in discerning and responding to user emotions. Overall, this research contributes to the ongoing endeavor of imbuing AI systems with emotional intelligence, paving the way for more nuanced and human-like interactions. © 2024 IEEE.

关键词： Chatbots

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Smart Vehicle Procurement System using Blockchain Technology 3

Smart Vehicle Procurement System using Blockchain Technology

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Kumar, Boddu Manoj Rajeswari, G. Duraipandian, Kavitha David, Shiela Dept. of Computer Science and Engineering with specialization in Blockchain Technology Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331527549

Blockchain technology has become more widespread in our lives revolutionizing various industries through improved security, transparency, and operational efficiency. Its decentralized ledger system is particularly effective in areas like finance and supply chain management ensuring data integrity and reducing the need for middlemen. This study explores how blockchain technology is used in the process of buying vehicles highlighting its benefits compared to methods. Traditional vehicle purchases involve a network of dealers, banks and regulators leading to inefficiencies, higher costs and potential fraud. The usual process involves steps like financing checking vehicle history and changing ownership. Each requiring extensive paperwork and third-party intervention. In contrast using blockchain for vehicle purchases can simplify things through contracts that automate tasks like verifying history securely transferring ownership instantly settling payments. The unchangeable nature of records ensures that all transaction data remains secure against tampering fostering trust between buyers and sellers. Furthermore, blockchain can cut costs significantly by removing the need for middlemen such, as escrow services and title companies while reducing burdens. The advanced security elements built into technology help reduce the chances of fraudulent actions like altering odometer readings or selling stolen cars. This study showcases a comparison illustrating how blockchain can simplify the process of buying vehicles offering an economical and secure experience. © 2025 IEEE.

关键词： Decentralized finance

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PraaKrum: A Practical Byzantine-Resilient Federated Learning Algorithm 16

PraaKrum: A Practical Byzantine-Resilient Federated Learning...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Kukreja, Prabhleen Mahendran, V. Indian Institute of Technology Tirupati Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350383119

Federated Learning (FL) is considered as a suitable paradigm for intelligent data analytics over Internet of Thing (IoT) devices. While the data-privacy preserving feature of FL is useful, the lack of data auditing abilities of the participating IoTs creates a potential attack surface. To this end, a potential attacker can perform data/model poisoning attacks on the FL. To protect from such attacks, a popular theoretically proven algorithm for FL namely, Krum [1] was proposed. From an implementation perspective, the Krum algorithm needs to be provided with apriori information such as the total number of attackers in each round, which is impractical. It is not feasible to know, in advance, which of the participating IoT clients are attackers. Furthermore, in the presence of mobile Parameter Server (PS) which stays in the WiFi coverage area consisting of stationary clients for an unknown time, the implementation of Krum algorithm in such practical setting is not investigated, to the best of our knowledge. With an aim to provide a practical implementation of a resilient FL framework, for the first time, this paper investigates the sensitivity of the attackers information towards the robustness offered by the Krum-based FL algorithm. The insights gained from the sensitivity analysis are used to develop a novel and Practical algorithm of Krum (PraaKrum) for FL for a WiFi network with mobile PS. The developed analysis is helpful in both understanding the key resilient characteristics offered by the Krum algorithm and providing the research community with a guideline towards the practical implementation of the attacker-resilient Krum-based FL algorithm in a mobile wireless setting. © 2024 IEEE.

关键词： Byzantine-resilience Federated learning insensitivity result Krum algorithm WiFi wireless IoT

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DubasAlert: AI-Powered Detection System for Dubas Infestation on Palm Leaves

DubasAlert: AI-Powered Detection System for Dubas Infestatio...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Nagaraju, Y. Venkatesh Uvce Bangalore University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350359688

In Middle Eastern countries, Dubas insects pose a significant threat, causing plant death by draining sap from date palm leaflets and fronds. This study presents a novel method for detecting Dubas insects at different stages of their growth. Existing models perform ineffectively and have large trained weights, making integration with edge devices difficult. To address these issues, we propose a pruned YOLOv7 model which is lighter and has fewer parameters, resulting in 75% lower FLOPs. Pruned Yolov7 outperforms baseline models with a mAP@0.5 of 80.1%. Our approach enables real-time detection and seamless integration into edge devices, resulting in practical solutions to combat Dubas insect infestations. © 2024 IEEE.

关键词： Plant diseases

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Smart Agriculture Inventory Management System Using Machine Learning Algorithms 1

Smart Agriculture Inventory Management System Using Machine ...

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1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Kanyal, Hoshiyar Singh Jain, Harshit Tyagi, Harsh Yadav, Satyarth Prakash ABES Institute of Technology Ghaziabad Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350353648

In the agricultural sector, smallholder farmers in India face significant challenges with post-harvest losses, fluctuating market prices, and unsustainable practices. This research proposes a mobile-based application designed specifically for farmers in region of India, focusing on specific crops. To reduce agricultural waste, the app features an optimal storage location based on crop type. To improve farmer income, the app includes a crop recommendation module that integrates historical yield data, weather forecasts, soil characteristics, and real-time market prices. Machine learning models, validated with field data, suggest high-yield, profitable crops and optimal sales timing. A market information hub provides real-time mandi prices and demand forecasts. With a user-friendly interface and visual explanations, the app addresses the technological constraints of smallholder farmers. This research aims to reduce agricultural waste, improve farmer income, and promote sustainable agriculture practices. © 2024 IEEE.

关键词： Agricultural economics

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