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Secure Rotation Invariant Face Detection System for Authentication

computers, Materials & Continua 2022年第1期70卷 1955-1974页

作者： Amit Verma Mohammed Baljon Shailendra Mishra Iqbaldeep Kaur Ritika Saini Sharad Saxena Sanjay Kumar Sharma Department of Computer Science&Engineering Chandigarh Group of CollegesMohali140317India Department of Computer Engineering College of Computer&Information ScienceMajmaah University11952Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering&TechnologyPatiala147004India Department of Computer Centre&Campus Network Facility Science Complex PO Central UniversityGachibowliHyderabad500046TelanganaIndia

Biometric applications widely use the face as a component for recognition and automatic *** rotation is a variable component and makes face detection a complex and challenging task with varied angles and *** problem has been investigated,and a novice algorithm,namely RIFDS(Rotation Invariant Face Detection System),has been *** objective of the paper is to implement a robust method for face detection taken at various *** to achieve better results than known algorithms for face *** RIFDS Polar Harmonic Transforms(PHT)technique is combined with Multi-Block Local Binary Pattern(MBLBP)in a hybrid *** MBLBP is used to extract texture patterns from the digital image,and the PHT is used to manage invariant rotation *** this manner,RIFDS can detect human faces at different rotations and with different facial *** RIFDS performance is validated on different face databases like LFW,ORL,CMU,MIT-CBCL,JAFFF Face Databases,and Lena *** results show that the RIFDS algorithm can detect faces at varying angles and at different image resolutions and with an accuracy of 99.9%.The RIFDS algorithm outperforms previous methods like Viola-Jones,Multi-blockLocal Binary Pattern(MBLBP),and Polar HarmonicTransforms(PHTs).The RIFDS approach has a further scope with a genetic algorithm to detect faces(approximation)even from shadows.

关键词： Pose variations face detection frontal faces facial expressions emotions

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Early Diagnosis of Rheumatoid Arthritis of the Wrist Using Power Doppler Ultrasound: A Review 1st

Early Diagnosis of Rheumatoid Arthritis of the Wrist Using P...

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1st EAI International Conference on Intelligent Systems and Machine Learning, ICISML 2022

作者： Asha, D. Priscilla Sharlet Hemalatha, R.J. Department of Biomedical Engineering Vels Institute of Science Technology and Advanced Studies Pallavaram Tamil Nadu Chennai6000117 India

ISBN: (纸本)9783031350771

Rheumatoid joint pain is ongoing severe infection that can influence joints as it were. This condition can harm different organ frameworks like skin, eyes, lungs, heart, and blood vessels. Rheumatoid joint pain, an immune system sickness, happens when the safe framework incidentally goes after its body tissues. Rheumatoid joint inflammation goes after the coating of the joints, causing a difficult expanding that can prompt bone deterioration and joint deformity. Ultrasound imaging is utilized for the early discovery of rheumatoid joint pain in the wrist. RA causes disfigurements in the patient's wrists, causing unbearable delicacy and enlarging in the joints. Clinical pictures, for example, X-beams, Ultrasound Power Dopplers assume a fundamental part in the early recognition of RA on the wrist. In any case, the as of late presented simulated intelligence (computerized reasoning) innovation further improves the capacities of imaging apparatuses. We support the exact determination of clinical experts. Picture catch utilizing simulated intelligence can extraordinarily assist with mechanizing the checking system, accelerate patient finding, and empower early identification and treatment to forestall distortions. computer-based intelligence can likewise further develop work productivity through precise determination. Furthermore, the computerised platform helps radiologists with chasing after clinical decisions (i.e.) about contamination following and prognosticate. We have in like manner analysed the different segmentation methodologies used in clinical image management. © 2023, ICST institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Deterioration

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Personalized Mental Health Analysis Using Artificial Intelligence Approach

Personalized Mental Health Analysis Using Artificial Intelli...

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Mathin, Shaik Chandra, Donthula Sharath Sunkireddy, Anudeep Reddy Varma, B.J.V. Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College Of Engineering Department Of Computer Science And Engineering Hyderabad India Chitkara University Institute Of Engineering And Technology Chitkara University Punjab India

ISBN: (纸本)9798350364828

With the help of artificial intelligence in personalized mental health, it enhances the quality and accessibility of mental health support. Mental health issues continue to be a global concern, and advancements in AI technology offer new avenues for providing tailored support to individuals seeking assistance with their mental well-being. Its purpose is to collect information from users regarding common ailments such as anxiety, depression, and stress-related problems in plain language, which may then be retrieved using natural language processing (NLP). As a result, it is critical to determine whether the individual is suffering from mental health issues or not. Once the person's mental health problem has been validated, the type of mental health disorder can be determined. Based on the information extracted, identify the disease, and offer therapy strategies. Users of this program can interact with specialists to seek guidance, which helps to alleviate anxiety, stress, and other disorders by reducing their health issues and worries. It takes a user-centric approach to mental health treatment, integrating the power of AI with personalized care. © 2024 IEEE.

关键词： Decision trees

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Recognition of Secure Data Transmission in Cloud Platform using Deep Learning 3

Recognition of Secure Data Transmission in Cloud Platform us...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Bhavya, R. Kumar, M. Guru Vimal Ramya, U.M. Janagi, R. Ganesan, M. Deepa, S. New Horizon College of Engineering Department of Computer Science and Engineering Bangalore India Vel Tech Rangarajan Dr. SangunthalaR&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Sri Krishna College of Engineering and Technology Deparment of Information Technology Coimbatore India Bannari Amman Institute of Technology Department of Computer Science and Engineering Erode India Hindusthan College of Engineering and Technology Deparment of Information Technology Coimbatore India Kongu Engineering College Perundurai Department of Computer Technology-PG Erode638060 India

ISBN: (纸本)9798350375190

The recognition of secure data transmission in a cloud platform requires the integrity of sensitive information with higher confidentiality. This is obtained using the aid of deep learning techniques. The robustness of the system is improved using a random forest algorithm. In secure data transmission, the deep learning algorithms are trained to adopt various patterns of communication with the identification of certain anomalies. They result in security threats. They involve suspicious user behaviour with unexpected information exchange. The overall accuracy and interpretability of the system are achieved using a random forest algorithm which combines multiple decision trees. They are used for handling the high-dimensional data and obtaining the relationship between complex patterns. They helps in the identification of various security threats in the data communication through cloud platforms. This helps in the automatic decision-making process during malicious behaviour. The obtained dataset contains both the secure and insecure datasets. The extracted features acts as an input for the random forest classifier. These features are analyzed by the random forest and provides information that helps to influence the decision-making process. The integrated approach improves the accuracy of the security threats with enhancing transparency in the automatic decision-making techniques. They provide trust in the security measures in the cloud platforms. The collaboration of deep learning with a random forest algorithm helps in obtaining secure data transmission. © 2024 IEEE.

关键词： Behavioral research

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Crop Quality Quantification: A Federated Learning CNN's Approach to Broccoli Leaf Disease Detection

Crop Quality Quantification: A Federated Learning CNN's Appr...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Suryavanshi, Ankita Mehta, Shiva Gopal, Lisa Thapliyal, Siddhant Jain, Vishal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India Sharda University Computer Science and Engineering Sharda School of Engineering and Technology U.P. Greater Noida India

ISBN: (纸本)9798350361537

This article proposes a thorough research study between federated learning and CNNs, where both methods are utilized for the detection and severity categorization of broccoli leaf diseases. The algorithm uses the data, the separation of four clients' enthused, to point out the severity of diseases among four categories that start from mild to critical illness. A federated learning system has used client data instead of a global model to train a learning model where privacy issues have not arisen. The study of the results revealed that the FedAvg algorithm-based federated learning method, which is precisely featured with that property, kept each individual's observation data as an origin point to create a highly effective global model. The research depended on macro-economic, micro-economic, and weighted averages to reflect the model's accomplishments at both local and international levels. For all the intensely local ratings whatsoever, the customers SB-1, SB-2, and SB-3 showed a macro average score of 92.17 and 96.49, respectively, at a swell of 96.64 and 97.1. These scores reflect that the model's accuracy and recall are improving, which is constantly witnessed among clients. Scores were calculated by burden weighting. Since the first computation of the score was 92.26, sb-1. In the long term, scores for sb-2, sb-3, and sb-4 trended upward, with sb-4 finally peaking at 97.08. After the weighted averages, the micro averages are statistically one in line;the outcome is 92.24 in sb-1 and 97.08 in sb-4. This invariably drives the model to the correct result, implying data consistency. All the local areas had a macro average score of 97.65, a micro score of 97.63, and a weighted average score of 97.63. © 2024 IEEE.

关键词： Federated learning

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Enhanced deep learning approach for text to image conversion using Lip movements 4

Enhanced deep learning approach for text to image conversion...

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4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Karthikeya, Andhoju Kumar, Alle Aniesh Manicharan, Chennuri Hariharan, Shanmugasundaram Kukreja, Vinay Prasad, Andraju Bhanu Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350307757

The process of utilizing deep neural networks to extract speech from voiceless video is known as lip reading. This study looks into how to improve the precision and dependability of lip reading to picture conversion by combining LipNet, a well-known deep learning model, with the idea of stable diffusion. LipNet uses convolutional and recurrent neural networks to understand the subtleties of lip motions during speaking. In order to give the lip reading process predictability and consistency, stable diffusion which is a mechanism that contributes to controlled spreading phenomena that is investigated in the proposed study here. LipNet and stable diffusion work together to provide insights on how to retain precision under a variety of circumstances, including difficult surroundings and a wide range of linguistic patterns. By assessing the influence of stable diffusion on the effectiveness of lip reading technologies, this research adds to the discussion on improving deep learning applications for visual comprehension and dialog. © 2024 IEEE.

关键词： Diffusion

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Unveiling time utilization in resource constrained environment

Unveiling time utilization in resource constrained environme...

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

作者： Rahul, Ch. Kousarr, Noushheen Yadav, T. Abhishek Keerthi, Pendam Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Chitkara University Chitkara University Institute of Engineering and Technology Punjab India

ISBN: (纸本)9798350359688

In response to the escalating challenges of resource-constrained environments, this research endeavors to provide a comprehensive analysis of Lightweight Cryptography (LWC). With the increasing prevalence of Internet of Things (IoT) devices and the growing need for secure communication in diverse settings, understanding cryptographic algorithms' performance becomes paramount. Existing analyses of LWC algorithms often lack a holistic evaluation, particularly in terms of certain performance dimensions. This research bridges this gap by meticulously examining a curated set of algorithms, including Ascon, Gift, Elephant, Tiny Jambu, Isap, Sparkle, PHOTON-Beetle, Romulus, and Grain. The study focuses on key performance metrics such as execution time, task clock cycles, and throughput, providing a nuanced understanding of these algorithms' efficiency in real-world scenarios. Innovatively, this research proposes novel ideas for enhancing the performance of LWC algorithms, extending beyond conventional security paradigms. By unveiling and comprehensively analyzing execution time, task clock cycles, and throughput, the study aims to provide actionable insights for optimizing cryptographic protocols. This research stands as a pivotal contribution to the evolving landscape of lightweight cryptography, offering practical solutions to enhance the efficiency and applicability of cryptographic algorithms in resource-constrained environments. © 2024 IEEE.

关键词： Clocks

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Analysis of optical networks in presence of nodes noise and crosstalk

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Journal of Optical Communications 2024年第3期45卷 547-554页

作者： Shukla, Rahul Deo Pratap, Ajay Suryavanshi, Raghuraj Singh Amity Institute of Information Technology Amity University Lucknow Campus Uttar Pradesh Lucknow India Department of Computer Science & Engineering Pranveer Singh Institute of Technology Kanpur India

Optical packet switching has gained lot of momentum in last decade due to the advantages of optical fiber over copper cables. Optical switching is beneficial in optical networks which form connections of links and switching nodes. In these high speed networks minimum delay and high throughput are two important parameters which are considered. To minimize network delay shortest path algorithm is used for route selections. In previous studies while choosing shortest path distance among various nodes is considered. In this work we have shown that it is necessary to consider both distance and number of hops while choosing path from source to destination to minimize power per bit used for the transmission. © 2021 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Optical switches

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Tutorial on Automated Trading using API 23

Tutorial on Automated Trading using API

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6th ACM India Joint International Conference on Data science and Management of Data, CODS-COMAD 2023

作者： Chakole, Dr. Jagdish Kurhekar, Dr. Manish Computer Science and Engineering Indian Institute of Information Technology Maharashtra Nagpur India Computer Science and Engineering Visvesvaraya National Institute of Technology Nagpur Maharashtra Nagpur India

ISBN: (纸本)9781450397988

Automation has played a significant role in many domains, and stock market trading is not an exception. Even retail traders can automate his/her trading strategy using API. A computer program doing trading is known as Algorithmic Trading. It eliminates inefficiency due to human emotions. Trading logic that decides when to buy and sell a stock is generally term as a trading strategy. The availability of large trading data has made it possible to automate the generation of dynamic trading strategies. Speed and accuracy are very vital aspects of profitable stock market trading. Algorithmic trading is far superior to manual trading in terms of speed and accuracy. In this tutorial, we demonstrate the automation of predefined trading strategies using Python API. We will also demonstrate the generation of trading strategies using Reinforcement learning, Deep learning, and various other domains in computer science. Validating the performance of any predefined trading strategy on historical data plays a significant role in its live performance and it is known as backtesting. Backtesting is the key feature of Algorithmic Trading. We will demonstrate backtesting of the trading strategies using a computer program on the Indian and American stock market data. © 2023 ACM.

关键词： Automation

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Research on the closed-loop supply chain of intelligent products considering government subsidies in the context of the internet of things

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Discover Internet of Things 2025年第1期5卷 1-20页

作者： Zhao, Jinghua Cui, Shaoyun Xu, Zheng School of Business University of Shanghai for Science and Technology Shanghai China School of Computer and Information Engineering Institute for Artificial Intelligence Shanghai Polytechnic University Shanghai201209 China

The rapid development of Internet of Things technology and the continuous improvement of consumer demand have spawned the emergence of intelligent products based on Internet of Things technology. The existing research on the closed-loop supply chain of intelligent products under the background of the Internet of Things still lacks consideration of different subsidy objects and recyclers. Therefore, for different subsidy objects in the three-stage closed-loop supply chain of intelligent products, a pricing decision model involving manufacturers, recyclers, retailers and consumers under the minimum standard supervision of recycling technology is constructed, and different recyclers are distinguished according to the characteristics of intelligent products. By comparing the profits of each subject in different models, the optimal model of government subsidy is obtained. It is found that under the four modes, subsidizing recyclers without self-recovery technology makes the total profit of the supply chain reach the optimal solution;capital recyclers can obtain the largest number of old intelligent product recycling by using self-recovery technology;when subsidizing manufacturers, the total profit and product recovery rate of the supply chain are at the bottom. In addition, recycling subsidies, subsidy impact coefficients and technical standards will affect the best profits of enterprises. Through the analysis of the closed-loop supply chain of intelligent products, the research provides theoretical support and decision-making basis for the supply chain members to formulate relevant strategies and the government to take relevant measures to promote resource utilization and environmental protection. © The Author(s) 2025.

关键词： Smart manufacturing

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