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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Feride Tanrikulu Timothy L. Haithcoat Grant J. Scott Matthew Foulkes Ilker Ersoy Institute for Data Science and Informatics University of Missouri Dept. Electrical Engineering and Computer Science University of Missouri Dept. of Geography University of Missouri

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Land valuations are used by buyers, sellers, regulators, and authorities to assess fair value. Urbanization demands a modern and efficient land valuation system. An alternative method that integrates geographic information systems and machine learning can produce more reliable, repeatable, and accurate valuations. The land’s value can vary significantly based on the parcel’s neighborhood and context. Geospatial analytics, remote sensing and vector information were integrated to predict land values in Springfield, Missouri, USA. A point geodatabase was assembled using calculated proximities, accessibility, and various index measures. Supervised machine learning models were trained using government-provided appraised land values as ground truth. The database approach integrated spatial context and socioeconomic data. Slight differences in performance between random forest (98%, 0.13) and gradient boosting (98%, 0.15) algorithms were found (Adj. R 2 , STD).

关键词： Regulators Machine learning algorithms Urban areas Spatial databases Vectors Reliability Socioeconomics

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A Face Pre-Processing Approach to Evade Deepfake Detector 1

A Face Pre-Processing Approach to Evade Deepfake Detector

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1st ACM Workshop on Security Implications of Deepfakes and Cheapfakes, WDC 2022, co-located with ACM AsiaCCS 2022

作者： Kim, Taejune Kim, Jeongho Kim, Jeonghyeon Woo, Simon S. Computer Science & Engineering Dept. Sungkyunkwan University Suwon Korea Republic of Dept. of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of Applied Data Science Dept. Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9781450391788

Recently, various image synthesis technologies have increased the prevalence of impersonation attacks. With the development of such technologies, damages to people such as defamation or fake news have also increased. Deepfakes have already evolved to the point, where people cannot easily distinguish fake from real. This leads to an urgent need for developing detection methods. Currently, in order to detect deepfakes, many deepfake datasets are widely used in deep neural networks. And several methods have been proposed and demonstrated to be effective in detecting deepfakes. In this work, we present pre-processing techniques such as face restoration, edge smoothing, face beautification to mitigate the artifacts of deepfakes and makes them appear more natural to humans, while lowering the deepfake detection performance. Through extensive experiments, our method can significantly lower the performance of the state-of-The-Art deepfake detectors and expose the vulnerability of deployed detectors. © 2022 ACM.

关键词： Deep neural networks

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Enhancing Blind Communication With Voice-Assisted Email

Enhancing Blind Communication With Voice-Assisted Email

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Expert Clouds and Applications (ICOECA), International Conference on

作者： C. Sasikala Rupalakshmi M Sameer Ahammad S Meghana U Harshad Ali M Dept. Computer Science and Engineering Srinivasa Ramanujan Institute of Technology Anantapur India Dept. Computer Science and Engineering(Data Science) Srinivasa Ramanujan Institute of Technology Anantapur India

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

Considering the key role of the internet in daily life, accessibility becomes crucial, especially for visually impaired individuals who heavily rely on it for accessing information. However, a significant portion of text materials on the internet remains inaccessible to blind users, limiting their opportunities for development and inclusion in various communities worldwide. Leveraging audio virtual environments, predominantly through screen reader technology, offers a notable advantage for blind individuals in accessing online applications like emails. This study presents a new design aimed at facilitating the email retrieval for blind users with the utilization of speech-to-text and text-to-speech technologies. This approach is particularly suitable for individuals with average human capabilities and a limited level of education, as it relies solely on interactive voice response for input, ensuring effective functionality for the proposed system.

关键词： Productivity Navigation Virtual environments User interfaces Electronic mail Text to speech Standards

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Predicting Customer Purchase Intent Using Logistic Regression: A data-Driven Approach

Predicting Customer Purchase Intent Using Logistic Regressio...

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Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： C. Rajarajachozhan G. Karthika A. Rajakrishnammal M. Mano P. Nithish Kumar E. Jayahari Dept. of Electronics and Communication Engineering Saveetha Engineering College Chennai Tamil Nadu Dept. of Artificial Intelligence and Data Science Saveetha Engineering College Chennai Tamil Nadu Dept. of Computer Science and Engineering Saveetha Engineering College Chennai Tamil Nadu

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynamic and extensive customer data, limiting their flexibility and precision. This project employs a machine learning methodology utilizing logistic regression to forecast customer intent based on demographic, transactional, and behavioral data. The proposed model analyses input features including age, browsing history, and previous purchases, employing sophisticated data preprocessing methods such as One-Hot Encoding and feature scaling to guarantee data integrity. Through hyperparameter tuning and the assessment of critical metrics including accuracy, precision, recall, and Fl-score, the system provides dependable and actionable insights. Real-time predictive capabilities enable businesses to customize customer interactions, facilitating targeted marketing and enhancing customer experience. This project underscores the capacity of predictive analytics to tackle real-world issues, facilitating data-driven decision-making and sustainable business development.

关键词： Logistic regression Adaptation models Accuracy Pipelines Companies Predictive models Real-time systems data models Predictive analytics Business

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Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification

arXiv

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arXiv 2024年

作者： Schuchardt, Jan Stoian, Mihail Kosmala, Arthur Günnemann, Stephan Dept. of Computer Science Munich Data Science Institute Technical University of Munich Germany Dept. of Engineering University of Technology Nuremberg Germany

Amplification by subsampling is one of the main primitives in machine learning with differential privacy (DP): Training a model on random batches instead of complete datasets results in stronger privacy. This is traditionally formalized via mechanism-agnostic subsampling guarantees that express the privacy parameters of a subsampled mechanism as a function of the original mechanism’s privacy parameters. We propose the first general framework for deriving mechanism-specific guarantees, which leverage additional information beyond these parameters to more tightly characterize the subsampled mechanism’s privacy. Such guarantees are of particular importance for privacy accounting, i.e., tracking privacy over multiple iterations. Overall, our framework based on conditional optimal transport lets us derive existing and novel guarantees for approximate DP, accounting with Rényi DP, and accounting with dominating pairs in a unified, principled manner. As an application, we analyze how subsampling affects the privacy of groups of multiple users. Our tight mechanism-specific bounds outperform tight mechanism-agnostic bounds and classic group privacy results. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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Enhancing Robotic Grasp Failure Prediction Using A Pre-hoc Explainability Framework*

Enhancing Robotic Grasp Failure Prediction Using A Pre-hoc E...

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IEEE International Conference on Automation science and engineering (CASE)

作者： Cagla Acun Ali Ashary Dan O. Popa Olfa Nasraoui Dept. of Computer Science & Engineering Knowledge Discovery & Web Mining Lab Next Generation Systems Group

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Enhancing the explainability of machine learning (ML) models is crucial for bridging their use gap for practical applications of robotic autonomy. The common standard for adding explainability has been to use a post-hoc explanation approach. However, post-hoc approaches have recently attracted criticism for their lack of transparency, specifically because the post-hoc methods learn a surrogate model after the predictive model has already been learned, which means that the explanations are not authentically explaining the model’s behavior. This study aims to add explainability to the task of robot grasping failure prediction using Factorization Machines as the predictive model and using a novel pre-hoc explainability framework to learn an explainable Factorization Machine model. Unlike post-hoc methods, pre-hoc explainability starts with learning the explainable model before training the black-box model and then provides guidance while learning the latter to make predictions that are faithful to the explanations through a regularization mechanism. Through a detailed case study, we explore the trade-off between prediction accuracy and explanation fidelity and show that our framework is able to make predictions that are more accurate than an explainable white-box model while simultaneously learning a model whose pre-hoc explanations achieve a high level of fidelity relative to the predictions. Results show that our framework can predict the robustness of the grasp with 83% accuracy while explaining that increased effort exerted in Joint 2 of Finger 3 contributes tremendously to producing grasp failure, which is in contrast to increased efforts exerted at Joint 2 of Fingers 1 and 2 and at joint 1 of Finger 3, that all lead to reducing grasp failure.

关键词： Training knowledge engineering Accuracy Fingers Grasping Predictive models Robustness Robots Standards Optimization

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Crafting Connections: Empowering Kondapalli Artisans through a Mobile Application

Crafting Connections: Empowering Kondapalli Artisans through...

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Intelligent Systems and Machine Learning Conference (ISML)

作者： Chinta Vara Prasad J V D Prasad Vallakati Navyasri Dept. of Artificial Intelligence and Data Science V R Siddhartha Engineering College Vijayawada India Dept. of Computer Science and Engineering VR Siddhartha Engineering College Vijayawada India

ISBN: (数字)9798350343878

ISBN: (纸本)9798350343885

Handicrafts hold historical significance in representing the essence of our nation's native culture. However, these handcrafted goods still need to be explored globally, and the manufacturers frequently need help connecting directly with larger markets and potential customers. The scope of this project is bound to Kondapalli Toys, also known as Kondapalli Bommalu, renowned wooden handicrafts originating from Andhra Pradesh, India. The current resources for resolving this issue are not easily available on the market, and there is a lack of a user-friendly application. A dedicated Android application is needed to strengthen the handicraft business. This application enables artisans and potential customers to communicate effortlessly, guaranteeing secure transactions, offering valuable data insights, and providing resources for skill and capacity development. The user interface for this application was developed using the Flutter framework, which prioritizes data security and is scalable and region-adaptive. Through this application, manufacturers can conveniently reach markets while customers have the opportunity to explore and connect with their businesses, allowing them to display their craft items to a global audience.

关键词： Technological innovation Sentiment analysis Toy manufacturing industry Globalization User interfaces Real-time systems Mobile applications Registers Monitoring Business

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Revolutionizing Public Transport: RFID-Enabled Occupancy Monitoring and Frequency Analysis System

Revolutionizing Public Transport: RFID-Enabled Occupancy Mon...

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2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Mageswaran, J. Uma Indumathi, G. Kalpana, A.V. Elangovan, G. Lalitha, S.D. Nalini, S. Sohanda, Mayank Kumar Dept. of Computer Science Engineering Amrita School of Computing Vengal Campus Tiruvallur DistTamil Nadu India Srm Institute Of Science And Technology Ramapuram India Srm Institute Of Science And Technology Department Of Data Science And Business Systems Kattankulathur India R.M.K Engineering College Department Of Computer Science And Engineering India Srm Institute Of Science And Technolog Department Of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350352689

Public bus stops in India are becoming more crowded due to the country's fast population expansion. People wait a long time for buses to come, then suddenly congregate around them when they do, packing the buses with people and pushing them up into the footboards, which causes accidents. An additional concern of overcrowding is theft. All of this is the result of numerous bus stops not having adequate information on when busses would arrive. The proposed work paves a very important role for the passengers. The passengers will be provided with the information of the arrival of next bus, seat occupancy and the total passengers inside the bus. The information about the seat occupancy, in-passengers and out-passengers is done with the help of Radio Frequency Identification (RFID) tags. The arrival of the next bus is determined by calculating the duration of the buses that are near using RFID readers placed in different bus stations. The count and the frequency will be interfaced in the web application. The passengers can check the application to know the occupancy and today's society where people can catch the right bus at the station and at the right time. This will solve the problems like waiting in bus stops and wasting time and going in a crowded bus. © 2024 IEEE.

关键词： Buses

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An Effective Crop Recommendation using Ensemble Classifier

An Effective Crop Recommendation using Ensemble Classifier

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Intelligent data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Ashok Reddy Kandula Jai Srinivas Vadapalli Srinivasa Sai Shanmukha Mannava Sai Seetharam Modugumudi Irfan Mohammad Dept. of Artificial Intelligence & Data Science Seshadri Rao Gudlavalleru Engineering College Gudlavalleru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Modern expectations for efficiency and sustainability are sometimes not addressed by the existing approaches in the continually changing environment of agricultural activities. In order to fully address these difficulties, research investigates how precision farming practices may be integrated while utilizing technological improvements. Study attempts to estimate optimal crop choices by assessing important characteristics including area, rainfall, temperature, and district-specific data, giving farmers the power to make well-informed and data-driven decisions. Precision farming lowers risks related to climatic unpredictability, increases output, and minimizes resource waste. By using the strategy, encourage resilience and innovation in the agricultural industry while bridging the gap between current farming practices and the sustainable agriculture of the future. Employing advanced algorithms including LR, Ridge Regression, DTs, and classifiers, achieved a remarkable 96% accuracy rate. Additionally, the proposed system offers real-time alerts via email or SMS, delivering timely advice and actionable insights to enhance agricultural sustainability and productivity.

关键词： Productivity Technological innovation Temperature distribution Rain Crops Agriculture Real-time systems Sustainable development Farming Resilience

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Indoor Navigation System for KCT Using AR Techniques

Indoor Navigation System for KCT Using AR Techniques

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Anitha P Madhav S Nishanth M V GowriShankar S Sanjai Kumar S Jaidev M V Dept. of Computer Science and Engineering Kumaraguru College of Technology Coimbatore TamilNadu Dept. of Artificial Intelligence and Data Science Kumaraguru College of Technology Coimbatore TamilNadu

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Moving around in confusing indoor spaces like malls, airport, campuses is very difficult if the setting is unknown. This system gives real-time turn-by-turn guidance on mobile phones using Unity with AR Foundation and NavMesh. LiDAR cameras enable accurate 3D mapping, and a GPS, Wi-Fi and Bluetooth beacon hybrid positioning system enables accurate pinpoint positioning in GPS-denied environments. The study seeks to improve user experience by simple, real-time guidance and context information as AR visualization. The system improves user disorientation and speeds up navigation speed by superimposition of directional signs over the real-world environment. Major conclusions highlight the precision and consistency of the system, specifically in vast indoor environments. The power of the system is that it can substitute conventional maps and signs to make the process of navigating seamless. Scalability and leveraging AI for smart routing and natural interaction will be addressed in subsequent work, a revolution of AR navigation technology. The study opens up a possibility for indoor navigation solutions to become more intuitive and user-centric.

关键词： Three-dimensional displays Laser radar Accuracy Indoor navigation Routing Airports Real-time systems Augmented reality Wireless fidelity Global Positioning System

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