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A Study on Medicinal Plant Leaf recognition Using Artificial intelligence 3

A Study on Medicinal Plant Leaf Recognition Using Artificial...

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3rd international conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Ayumi, Vina Ermatita, Ermatita Abdiansah, Abdiansah Noprisson, Handrie Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Universitas Mercu Buana Faculty of Computer Science Jakarta Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce these resources, some researchers propose to implement artificial intelligence technology. This paper aims are to conduct a systematic literature review of medicinal plant leaf recognition published in the last two years (2019-2020) from IEEE, Springer and Science Direct. We obtained 15 studies in the field of medicinal plant leaf recognition using artificial intelligence. The dataset used for medicinal plant leaf recognition is mostly used private dataset, however, there are public dataset named Leaf, Flavia, Swedish dataset. We also found robust method that can be used for medicinal plant leaf recognition is Multichannel Modified Local Gradient pattern (MCMLGP) and Gray Level Co-Occurrence Matrix (GLCM) as feature extraction;and Convolutional Neural Network (CNN), Multi-Layer Perceptron trained with Backpropagation algorithm (MLP-BP), Support Vector machine (SVM), and Transfer Learning (VGG19) as classifier. © 2021 IEEE.

关键词： Image processing

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The Evolutionary Game Research on the Development of New Financial Services Infrastructure under the "Double Cycle" Development pattern 3

The Evolutionary Game Research on the Development of New Fin...

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3rd international conference on machine Learning, Big Data and Business intelligence (MLBDBI)

作者： Jing, Luru Feng, Minfu Sichuan Univ Sch Math Chengdu 637000 Sichuan Peoples R China

ISBN: (纸本)9781665417907

"New infrastructure" is a new concept relative to "old infrastructure". As an emerging industry, it has been based on the infrastructure construction of cutting-edge science and technology. This paper takes enterprises and financial institutions as the research objects, and explores the evolutionary game between financial institutions and enterprise groups from the perspective of group game. In this paper, the replication dynamic equation model in evolutionary game theory is constructed, and the parameters are analyzed. The results show that the relationship between the total cost of "actively providing financial services" and the total cost of "passively providing financial services" and the income of "actively participating in financial activities" plays a decisive role in the existence of evolutionary game strategy between the two groups. Finally, according to the model analysis and the conclusion, based on the "double cycle" development pattern, this paper puts forward some countermeasures and suggestions for the construction of new infrastructure market, in order to provide new ideas for the high-quality development of China's economy.

关键词： financial institutions enterprises new infrastructure double cycle

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Virtual resurrection leveraging 3D modeling for digital preservation of an ancient educational institution 3

Virtual resurrection leveraging 3D modeling for digital pres...

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3rd international conference on Visual pattern Extraction and recognition for Cultural Heritage Understanding, VIPERC 2024

作者： Anuj, Sreedharan Santheep, Wilson Suthakaran Alfred Daniel, John William Santhosh, Rajendran Parthasarathy, Velusamy Karpagam Academy of Higher Education Tamil Nadu Coimbatore641021 India

Nowadays, advanced 3D modeling software lets us see, explore and learn about historical sites like never before. Preserving our cultural heritage for future generations means documenting ancient sites accurately and enhancing user experience in virtual visits and education. This paper describes a method to digitally reconstruct and restore Nalanda University, a UNESCO World Heritage site. We collect data from historical records, old maps and photographs, then segregate the ruins based on their importance and features. We use Blender and Maya to create and optimize 3D models to get an accurate virtual representation of Nalanda. This digital model will give us valuable insights into the university's history and culture, a resource for researchers, historians and the public. © 2024 Copyright for this paper by its authors.

关键词： Digital elevation model

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Exploration of Contour Coding and Its Application in Digital Image Processing 3

Exploration of Contour Coding and Its Application in Digital...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Little Femilin Jana, D. Kadam, Prema S. Sharma, Neeraj Garg, Avni Acharjya, Kalyan Venkadeshwaran, K. Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar562112 India

ISBN: (纸本)9798350319125

Photograph processing is a discipline of laptop science that concentrates on manipulating digital photos and using algorithms to recognize and beautify the photo's quality. Contour coding is a powerful approach used in virtual picture processing that allows one to increase, shop, and examine virtual snapshots from a combination of strategies like aspect detection, morphological processing, and segmentation. Contour coding aims to reduce complex virtual pix to a fixed of fundamental symbolic features that may be created, stored, and manipulated without loss in quality or element. Applications of contour coding are specially used for item reputation, segmentation, spatial pattern reputation, and scientific photograph processing. This newsletter offers the theory and fundamentals of contour coding and explores its software in actual-world virtual picture processing scenarios. We speak about the significance of contour coding and present a short evaluation of existing algorithms and improvement techniques used to achieve virtual photograph processing desires. We additionally gift the advances and challenges of contour coding and how it could form the future of digital picture processing. © 2023 IEEE.

关键词： challenges development fundamentals processing segmentation

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Data Urbanity: Smart City Evolution Through IoT and Data Science 3

Data Urbanity: Smart City Evolution Through IoT and Data Sci...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Singh, Ajay Kumar, Manni Chandigarh University Department.of Computer Science and Engineering Punjab Mohali India

ISBN: (纸本)9798350343632

The rapid increase in population density in urban cities has created a demand for suitable infrastructure and services to meet the needs of urban residents. To address this demand, urban planners and developers are turning to data science for assistance in creating smart city solutions. The Internet of Things (IoT) has played a significant role in the application of data science in urban planning, as IoT devices such as sensors and smart devices provide vast amounts of data that can be used to gain insights into the operations of the city and make data-driven decisions to enhance its productivity, efficiency, and overall quality of life. This paper provides a general overview of data science in urban planning for smart city development. It highlights the importance of data science in urban planning and the role it plays in creating smarter, more effective cities. By applying data analytics, machine learning, and other data science approaches, urban planners can gain insights into various aspects of urban life, including traffic patterns, energy usage, and public safety. These insights can then be used to develop strategies that improve traffic flow, reduce energy waste, and enhance overall quality of life in cities. The study aims to describe the function of data science in urban planning, examine case studies and best practices, discuss the challenges and limitations associated with applying data science in urban planning, and provide suggestions for further research and advancements in the field. By investigating how data science can be effectively used in urban planning for smart city development, this study contributes to the growing body of knowledge on creating more sustainable and livable cities. © 2023 IEEE.

关键词： Artificial intelligence Biomarkers cardiovascular disease Computed Tomography (CT) Data analysis Deep learning Diagnostic methods Early detection Electrocardiogram (ECG/EKG) Health informatics heart disease machine learning Magnetic Resonance Imaging (MRI) Medical imaging Predictive modeling Remote monitoring Risk assessment Signal processing Ultrasound Wearable devices

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Analysis of Bangla Transformation of Sentences Using machine Learning 1

引用

4th international conference on Deep Learning, Artificial intelligence and Robotics, ICDLAIR 2022

作者： Das, Rajesh Kumar Sammi, Samrina Sarkar Kobra, Khadijatul Ajmain, Moshfiqur Rahman khushbu, Sharun Akter Noori, Sheak Rashed Haider Daffodil International University Dhaka1341 Bangladesh

ISBN: (数字)9783031303968

ISBN: (纸本)9783031303951

In many languages, various language processing tools have been developed. The work of the Bengali NLP is getting richer day by day. Sentence pattern recognition in Bangla is a subject of attention. Additionally, our motivation was to work on implementing this pattern recognition concept into user-friendly applications. So, we generated an approach where a sentence (sorol, jotil and jougik) can be correctly identified. Our model accepts a Bangla sentence as input, determines the sentence construction type, and outputs the sentence type. The most popular and well-known six supervised machine learning algorithms were used to classify three types of sentence formation: Sorol Bakko (simple sentence), Jotil Bakko (complex sentence) and Jougik Bakko(compound sentence). We trained and tested our dataset, which contains 2727 numbers of data from various sources. We analyzed our dataset and got accuracy, precision, recall, f1-score and confusion matrix. We get the highest accuracy with the decision tree classifier, which is 93.72%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Unexpected Alliance of Cardiovascular Diseases and Artificial intelligence in Health Care 3rd

Unexpected Alliance of Cardiovascular Diseases and Artificia...

引用

3rd international conference on machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021

作者： Anand, Rishika Reddy, S.R.N. Kumar, Dinesh Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for Women Kashmere Gate Delhi110006 India Department of Pediatrics Dr. Ram Manohar Lohia Hospital Delhi India

ISBN: (纸本)9789811958670

In spite of having significant advances in medical field for diagnosis and treatment purposes, still there are lack of diagnosis methods for cardiovascular diseases which causes high mortality and morbidity. These days, cardiovascular diseases are getting complicated. People between the ages of 40–60 are mostly affected due to heart disease. The current state of digital health and artificial intelligence is useful for cardiovascular disease diagnosis. So, this research provides the accurate classification of patients suffering from cardiovascular disease or not. To improve and optimize the diagnosis methods for cardiovascular disease, artificial intelligence (machine learning and deep learning) has the ability to change the way of cardiology practicing. Various machine learning and deep learning algorithms, i.e., artificial neural network, adaptive boosting, XGBoost, random forest, decision tree, Naïve Bayes, stochastic gradient descent, K-nearest neighbor, logistic regression, are used in this research. Previously, maximum accuracy obtained by the researcher is 92% while using the Cleveland heart dataset. In this, AdaBoost, XGBoost, ANN, and decision tree give the maximum accuracy, i.e., 100%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Adaptive boosting

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Research on Anti-telecom Fraud Based on Artificial intelligence and Edge Computing

Research on Anti-telecom Fraud Based on Artificial Intellige...

引用

Electrical Engineering, Big Data and Algorithms (EEBDA), IEEE international conference on

作者： Peng Fang Qinguo Fang Shandong Branch of China Mobile Communication Group Design Institute Co. LTD Jinan China

This paper studies the artificial intelligence method based on the collaboration of edge and terminal, integrates the complementary advantages of the local computing and strong computing power of the two, realizes the characteristic recognition of telecom fraud behavior, and realizes the accurate and real-time anti-telecom fraud. By constructing a telecom fraud identification and defense system based on deep learning, the whole life cycle from post-analysis to pre-warning, in-process reminder and even blocking, post-monitoring feedback is realized, and the level of anti-telecom fraud technology is improved.

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Discriminatory Expressions to Improve Model Comprehensibility in Short Documents 3rd

Discriminatory Expressions to Improve Model Comprehensibili...

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3rd international conference on pattern recognition and Artificial intelligence, ICPRAI 2022

作者： Francisco, Manuel Castro, Juan Luis Department of Computer Science and Artificial Intelligence University of Granada Granada Spain

ISBN: (纸本)9783031090363

Microblogging sites are being used as analysis avenues due to their peculiarities (promptness, short texts..). Lately, researchers have focused mainly in classification performance rather than interpretability. When the problem requires transparency, it is necessary to build interpretable pipelines, and even though, resulting models are too complex to be considered comprehensible, making it impossible for humans to understand the actual decisions. This paper presents a feature selection mechanism that is able to improve comprehensibility by using less but more meaningful features. Results show that our proposal is better and the most stable one in terms of accuracy, generalisation and comprehensibility in microblogging context. © 2022, Springer Nature Switzerland AG.

关键词： Feature extraction

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Applications of ML/AI for Decision-Intensive Tasks in Production Planning and Control 3

Applications of ML/AI for Decision-Intensive Tasks in Produc...

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3rd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Elbasheer, Mohaiad Longo, Francesco Nicoletti, Letizia Padovano, Antonio Solina, Vittorio Vetrano, Marco Univ Calabria Dept Mech Energy & Management Engn DIMEG Arcavacata Di Rende Italy CAL TEK Srl Arcavacata Di Rende Italy

The fast-growing literature corpus of industry 4.0 in the last years also reflects the various applications of Artificial intelligence (AI) and machine Learning (ML) in the manufacturing domain. This paper conducts a literature survey to infer patterns and correlations within this scientific domain. This analysis aims to identify the knowledge gaps within the literature of ML/AI-enabled manufacturing systems. Therefore, the objective of this study is twofold;first, we aim to identify commonalities and general trends in AI/ML-enabled manufacturing systems. Secondly, we map the various application areas of AI/ML-based Production Planning and Control (PPC). To this end, an overall analysis of the keywords highlighted four major scientific scopes for ML/AI in manufacturing systems. Moreover, further investigation of this literature corpus was made to identify the different applications for AI/ML to enhance decision-making in PPC. Based on this analysis, three major pillars were identified as potential areas for AI/ML-enabled PPC for decision intensive tasks: dynamic scheduling, performance evaluation and monitoring, and automated process control. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： Artificial intelligence machine Learning Production Planning and Control Dynamic Scheduling Performance Evaluation and Monitoring Process Automation

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