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An investigation on feature and text extraction from images using image recognition in Android

Materials Today: Proceedings 2022年 51卷 798-802页

作者： Brijeshkumar Y. Panchal Gaurang Chauhan Sandipkumar R. Panchal Urvashi M. Chaudhari Department of Computer Science and Engineering DEPSTAR CHARUSAT Charotar University of Science and Technology (CHARUSAT) CHARUSAT campus Changa 388421 India ITsouls Vadodara India Associate Professor & I/C Principal Knowledge Institute of Technology & Engineering Gujarat India Department of Computer Engineering Sardar Patel College of Engineering Bakrol-Anand Gujarat India

In today’s era, there is a huge rise in demand for the data and information available in a printed medium. To resume time, cost, and energy, we have been developing numerous technology. One of them, convert JPG, JPEG, or PDF softcopy into text, this process calls Text extraction. Identification of characters and detection of words and texts is again an upfront challenging task. This paper is focused on an investigation of feature and text extraction from images using image recognition in Android. In this era of Research and technology, Image processing has become one of the most critical fields. Using a number of researchers' papers, we are going to study appropriate methods or algorithm, their accuracy, a key feature of each paper. All research papers going to study in the context of Android technology.

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Intelligent Analysis of Big Data in the information Flow

Intelligent Analysis of Big Data in the Information Flow

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information Computing and Processing (ICP), Seminar on

作者： Petr V. Chetyrbok Marina A. Shostak Candidate of Science Engineering and Associate Professor at the Department of Computer Studies and Information Technologies V.I. Vernadsky Crimean Federal University Simferopol Russia Graduate student at the Faculty of Tourism and Service Sochi State University Sochi Russia

The article considers the use of AI methods for creation of a knowledge base in the field of recreation using a national interactive map of local cultural trends. The map contains thousands of brands classified into 9...

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Applications of Artificial Intelligence in Biomedical Image Processing 2

Applications of Artificial Intelligence in Biomedical Image ...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Rajeyyagari, Sivaram Hung, Bui Thanh Chakrabarti, Prasun Shaqra University College of Computing and Information Technology Department of Computer Science Shaqra Saudi Arabia Thu Dau Mot University Data Analytics and Artificial Intelligence Laboratory Engineering Technology Faculty Thu Dau Mot Viet Nam Provost and Institute Endowed Distinguished Senior Chair Professor Techno India Njr Institute of Technology Rajasthan India

ISBN: (纸本)9781665400527

The biomedical applications of nanoparticles are growing in recent years. The uses range from diagnostic to therapeutic purposes, and researchers are constantly introducing new ways. Biosensors, miniaturization techniques, surface enhancement in implantable biomaterials, and better nanofibers in medical textiles are some of the contributions of biomedical nanotechnology. Therapeutic (medical) imaging successfully maps the anatomy of the human body. Image enhancement, analysis, categorization, and image based representation are all possible areas of computer processing and analysis of medical images. Therapeutic image understanding uses computer vision, applied mathematics, signal analysis, and artificial intelligence to recognise objects in medical images. Image processing is the use of computer algorithms to manipulate digital images. Hand-held transducers emit and receive pulsed acoustic waves for medical ultrasound imaging. In this study, a computer-aided diagnosis method is developed to help cytotechnicians locate and classify aberrant cells in cervical cytology images. With the outcomes of morphological and statistical edge based segmentation are compared to traditional segmentation techniques. The proposed segmentation methodology outperforms the other methods. This proposed technique's segmentation accuracy is 98%. © 2022 IEEE.

关键词： Artificial intelligence

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A Novel Forward Filter Feature Selection Algorithm Based on Maximum Dual Interaction and Maximum Feature Relevance(MDIMFR) for Machine Learning

A Novel Forward Filter Feature Selection Algorithm Based on ...

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International Conference on Advanced computer Control, ICACC

作者： M A Anitha K K Sherly Assistant Professor of Computer Science College of Engineering Cherthala Kerala India Associate Professor of Information Technology Rajagiri School of Engineering & Technology Kerala India

ISBN: (纸本)9781665439206

In the last few decades, Feature selection is one of the most challenging and open problem to researchers. The rapid progress in computational techniques causes the generation and recording of data in huge size. Though there exists various feature ranking methods, the processing of data is still a challenging task due to its computational complexity. The filter method has many advantages over the wrapper method. The filter methods are classifier independent and have better computational efficiency. Here, a subset of features is selected based on a certain goal function. Most of these goal functions employs the principle of information theory. Most of the algorithms in earlier studies addressed two factors, that is, maximization of relevancy and minimization of redundancy without considering the interaction among the features. This paper developed a new forward filter feature selection algorithm based on mutual information known as Maximum Dual Interaction and Maximum Feature Relevance(MDIMFR). This method considers all the three factors: relevance, redundancy, and feature interaction. This method is experimented on three datasets and compares the performance with existing methods. The results show that MDIMFR outperforms the existing competitive feature selection methods of recent studies: mRMR, JMIM and CMIM. MDIMFR also achieves good stability in average classification accuracy for a certain number of features, say k and above. Hence, these k features can be considered as an optimal feature set.

关键词： Machine learning algorithms Redundancy Filtering algorithms Feature extraction information filters Minimization Filtering theory

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IoT Based Human Biometric System Using Alcohol Level Detection for Driver Security

IoT Based Human Biometric System Using Alcohol Level Detecti...

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Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), International Conference on

作者： Anurag Sinha Nitish Kumar Amrita Ticku Vyom Modi Meghal Shah Kapil Shrivastava School of Computing and Information Sciences IGNOU New Delhi India Department of Computer Science Lovely Professional University Phagwara Punjab India Bharti Vidyapeeth's College of Engineering India India Faculty of Engineering Marwadi Education Foundation Rajkot Gujarat India Department of Computer Science & Engineering Charotar University of Science & Technology Gujarat India Assistant professor Department of computer engineering and applications GLA University mathura India

In today's society, driving after intoxication has become a major factor in traffic accidents. It is common knowledge that operating a vehicle while intoxicated is a major contributing factor in a significant number of accidents. The effects of drunk driving go beyond the drunk driver; they also affect other drivers and passengers in the same vehicle. As a result, this growing threat needs to be addressed immediately. Our project's goal is to create a system that uses the Internet of Things (IoT) to find traces of alcohol in someone's breath and apply preventive measures in order to effectively address this issue. Although there are laws against drunk driving, it is difficult to enforce them widely because law enforcement cannot constantly be present on the roads to spot drunk drivers. This restriction increases the chance of accidents significantly. In order to reduce future risks, a trustworthy system that can recognize and discourage drunk drivers is urgently needed. Drunk driving deaths are increasing, so we need to figure out how to reduce these kinds of deaths. The breath analyzing sensor used in the suggested system is the MQ-3, which calculates the breath alcohol content of an individual. The amount of alcohol that is allowed in the blood in India is 0.03. The engine won't start if the person's blood alcohol content is higher than this limit, making it impossible for them to drive. Additionally, the system will send an alert, possibly through a Raspberry Pi, to a friend or relative, providing the exact location using GPS coordinates. This notification serves as a precautionary measure to keep others informed about the situation. Implementing such a system can contribute significantly to reducing accidents related to alcohol consumption. In conclusion, detectors like the one proposed in this project hold immense significance in preventing the loss of life and property caused by reckless driving under the influence of alcohol.

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Dimensional Reduction Method based on Big Data Techniques for Large Scale Data

Dimensional Reduction Method based on Big Data Techniques fo...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Makhan Kumbhkar Pranjal Shukla Yashwardhan Singh Rohib Adrianto Sangia Dharmesh Dhabliya Department of computer science Christian Eminent College Indore India Data Engineering Associate Accenture Solutions Pvt. Ltd. Indore India IAIN Ambon Vishwakarma Institute of Information Technology Pune India

In the age of big data, analysing complex and enormous amounts of data costs time and money and might result in mistakes and misunderstandings. Therefore, bad inference and decision-making, and occasionally irreversible and catastrophic occurrences, could result from imprecise and mistaken reasoning. On the other hand, effective administration and use of priceless data can considerably expand knowledge and lower costs through preventive measures. Time-to-event and survival data analysis are the cornerstones of risk assessment in this area and play a crucial part in estimating the likelihood of numerous occurrences, including the failure of a device or component. As a result, before beginning any analytic process, it is desirable to apply appropriate approaches to effectively reduce large-scale, huge, and complex data, especially in terms of variables. To minimize the abovementioned decision-making challenges and to make survival data and failure analysis easier, we offer an applied data reduction strategy in this research that enables us to obtain appropriate multiclass classification in large dimensionality data and huge datasets. In order to estimate the risk in addition make decisions in the context of a complex analysis of big volume in survival analysis, this research presents an applied analysis data and attribute selection methodology.

关键词： Costs Scalability Decision making Big Data Feature extraction Encoding Cognition

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Any Bluetooth device can be hacked. Know how?

Cyber Security and Applications

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Cyber Security and Applications 2024年 2卷

作者： Muraleedhara, Prathibha Christo, Mary Subaja J, Jaya Yuvasini  D College of Technology – Information Security and Program Management University of Houston 77204 TX United States Department of Networking and Communication School of Computing SRM Institute of Science and Technology Kantankulathur Chennai India Department of Electronics and Communication Engineering Hindustan College of Engineering and Technology India Assistant Professor Department of Computer Science and Business Systems Thiagarajar College of Engineering Madurai 625015 India

In today's world, Bluetooth technology is integrated into almost every device we use, from wireless headsets, mice, and keyboards to cars and smart home devices. But with the convenience of this technology comes the risk of privacy and security breaches. Each Bluetooth device has potential vulnerabilities that cybercriminals can exploit and take advantage of. It is important to create awareness about various Bluetooth vulnerabilities, exploits, and ways to prevent them. This article examines the dark side of Bluetooth technology by explaining how hackers can find ways to bypass the advanced security features of laptops, phones, cars, or smart home devices to compromise the devices and steal personal sensitive data. Whether it is a casual user of Bluetooth technology or a business owner with multiple devices, understanding these risks is crucial to protecting yourself and your information. This article begins by explaining the basics of Bluetooth technology and how it works. Followed by a list of security risks involved while using Bluetooth and finally, it highlights the best practices to protect the devices and the data they contain. © 2024

关键词： Ad hoc networks and security risk Bluetooth Exploit Threat Vulnerability

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IoT based Power and Water Theft Detection in Urban Cities

IoT based Power and Water Theft Detection in Urban Cities

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Praful V. Nandankar G.N.R. Prasad M. Lakshminarayana Mr. Doddabasappa N G. Satish Ramya Maranan Assistant Professor Department of Electrical Engineering Government College of Nagpur Maharashtra India Sr. Asst. Professor Department of Master of Computer Application Chaitanya Bharathi Institute of Technology (A) Hyderabad India Assistant Professor Department of Medical Electronics Engineering M S Ramaiah Institute of Technology Karnataka India Assistant Professor School of Electrical and Electronic Engineering REVA University Bengaluru Karnataka India Associate Professor Department of Electrical and Electronics Engineering Sree Dattha Institute of Engineering and Science Sheriguda Ibrahimpatnam Hyderabad Telangana India Assistant Professor Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai India

Many people in metropolitan areas have experienced problems with energy and water shortages. Some people used modern technologies and advancements to theft water and power illegally. Because the planet absolutely needs both water and power. Currently, the Internet of Things (IoT), smart meters, smart pipelines, and smart homes are being heavily integrated to replace traditional systems for detecting theft activities. This can be digitizing both the meter readings and the data that has been gathered. Wireless technology may be used to collect and analyze the data, which helps to reduce the need for physical labor. In this project, we suggested creating an IoT-based system for water and power theft detection. The proposed project aims to design a system to monitor the amount of power and water used by the people and indicates if water and electricity theft activities happen. This research study offers a user interface system to help people to monitor whether anyone is stealing their water or power. This study employs a hardware like voltage sensors, current sensors, flow sensors, and additionally, the Arduino IoT cloud to enable remote control and monitor the water and power usage.

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Usability Evaluation of Kids’ Learning Apps

Usability Evaluation of Kids’ Learning Apps

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Business Analytics for technology and Security (ICBATS), International Conference on

作者： Amer Ibrahim Murad Al-Rajab Khalid Hamid Muhamamd Aqeel Salman Muneer Mehvish Parveen Maryam Saleem College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates Assistant Professor Computer Scienc and IT College of Engineering Abu Dhabi University Department of Computer Science Superior University Lahore Pakistan Department of Software Engineering Superior University Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan School of Computer Science NCBAE Lahore Pakistan

The main objective of learning applications is to use modern electronic technologies to impart knowledge, communicate knowledge, and Direct learning models with their learning activities in a timely and effective manner. The preponderance of the apps were designed to up-skill the kids in the fundamentals of letters and numbers. Generally, they were grounded and practice skills in nature, based on a lack of abilities in critical thinking, favoring parrot-fashion skills, and contributing to a deep conceptual comprehension of more specific concepts are unable. By using appropriate evaluation methodologies, the purposed study observes essential characteristics and aspects that affect the usability of interfaces. An evaluation of the app's features will figure out to ensure user contentment. When a kid interacts with a learning interface, the ease of use provided by the interface is validated. Because a large number of the apps were designed to train kids’ fundamentals of alphabetic and numeric. The focus of this research is to see whether self-proclaimed learning apps for kids are built according to developmentally appropriate standards to help kids in formal and informal learning settings develop socially, emotionally, and academically.

关键词： Electronic learning User interfaces Security Usability Standards Business

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AI Framework for Keys Instruction and Music Notation

AI Framework for Keys Instruction and Music Notation

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Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Krishnaraj Rao N S Smitha GL P. S. Ramesh Nandhini T J P. Nagaveni A Balaji Assistant Professor Department of Information Science and Engineering Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT) Nitte Karnataka India Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Science (SIMATS) Chennai India Department of CSE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Saveetha School of Enginnering Saveetha Institute of Medical and Technical Science – SIMATS Saveetha University Chennai India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Department of IT Panimalar Engineering College

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

The study of artificial intelligence focuses on the principles that guide all human intellectual endeavors. The integration of several academic disciplines, including as computer science, philosophy, politics, linguistics, systems engineering, neurophysiology, and behavioral science, has allowed it to grow. This article will describe how to build an intelligent machine, consisting of both hardware and software, that can replicate and exceed the abilities of the human brain in order to handle complicated issues that need specialized knowledge. It will specifically examine how to more effectively use artificial intelligence support systems into piano instruction. An Introduction, an oral language and music-assisted education system based on the ARM and SA algorithm, is proposed by this study in order to ascertain the implementation principle guiding the functioning of the piano automation recording system. It also delves deeply into the theory and operation of automated music recording systems, compiling and evaluating data that these systems generate via internal databases. is an effort to improve music education via the use of artificial intelligence support systems. The results of the experiment show that the training system for the automated notation algorithms for playing the piano and songs has a 56.81 and fast growing machine learning auxiliary technology utilization rate. Thus, we may infer that using an AI support system is necessary while teaching performance piano and automated notation.

关键词： Training Machine learning algorithms Education Music Machine learning Software Recording Multiple signal classification Telecommunication computing Artificial intelligence

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