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Decoding the Devanagari - Handwritten Hindi Recognition Using Deep Learning Methodology

Decoding the Devanagari - Handwritten Hindi Recognition Usin...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Kukade, Jyoti Pawar, Rahul Singh Rai, Ishan Patidar, Megha Jain, Khushi Pandit, Deepa Medi-Caps University Department of Information Technology Indore India

ISBN: (纸本)9798350388800

Recognizing text contained within images holds increasing significance as digital content incorporates more visual elements. The preservation and digital conversion of hand-written manuscripts are pivotal for their accessibility and integration with computing systems. Hindi, scripted in Devanagari, ranks as the world's third most prevalent language. However, research on optical character recognition for handwritten languages such as Hindi often lags behind that of English. This study attempts to address this disparity by presenting a method that employs Convolutional Neural Networks to identify handwritten Hindustani characters. The model, comprising eighteen layers, attained a 98.8% accuracy rate when trained on the Kaggle-provided Devanagari Character Set Classification dataset, encompassing over 92,000 images. Leveraging the Rectified Linear Unit (ReLU) and Leaky ReLU activation functions, the Adam optimizer, and categorical cross-entropy loss, the model effectively categorizes characters. This approach not only showcases its proficiency in accurately identifying handwritten Hindi characters but also ushers in new avenues for exploration and application within this domain. In future, advanced models like RNN, CNN, and LSTM can be harnessed to comprehend entire statements and beyond. © 2024 IEEE.

关键词： Convolutional neural networks

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Low-Light Image Dehazing with Variational Enhancement Model 8

Low-Light Image Dehazing with Variational Enhancement Model

引用

8th international conference on robotics and Automation engineering, ICRAE 2023

作者： Yan, Chao Gao, Yin Li, Hao Li, Jun Quanzhou Institute of Equipment Manufacturing Chinese Academy of Sciences China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China China Fujian Institute of Research on the Structure of Matter University of Chinese Academy of Sciences China

ISBN: (纸本)9798350327656

Low-light image dehazing is a challenging and demanding task. Existing nighttime dehazing methods often suffer from issues like halo artifacts, color shifts, and amplified noise. To obtain natural haze-free images, this paper proposes a simple yet effective dehazing method based on a variational enhancement model. First, we reduce the influence of artificial light sources commonly found in low-light hazy images through glow correction. Then, the variational model based on cosine-gaussian is constructed to enhance the brightness of low-light hazy images and make the details more prominent. Finally, various factors such as the dark channel, channel difference, and brightness features are considered to solve the atmospheric scattering model and obtain refined haze-free images. Quantitative and qualitative comparisons validate the superior performance of the proposed low-light dehazing method compared to state-of-the-art approaches. Furthermore, the proposed method also demonstrates significant effectiveness in daytime image dehazing. © 2023 IEEE.

关键词： Luminance

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Smart Surveillance: Real-Time Object Detection and Recognition with Interactive Polygon Region Using Deep Learning

Smart Surveillance: Real-Time Object Detection and Recogniti...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Krishnan, Unni Kalaimani, Thyagarajan Sethuraman, R. Sathyabama Institute Of Science And Technology Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

The Traditional Surveillance system lacks the capability to focus on particular region at a time during the surveillance. This cause important detail in that region to be missed out and go unnoticed. This is a major issue as it causes security concern. Detection of any objects in that region should be done in real-time. The proposed system allows the user to create a polygon region in area of interest in the video and by using the capability of YOLOv8, which stands for You Only Look Once Version 8 this system can detect the object and classify them and then converting to csv file. By allowing the users to create the polygon region it gives the surveillance camera capability of highly precise monitoring. This system helps to monitor the regions that changes dynamically. Changing Traditional surveillance system as a whole can be expensive and time consuming. Our system helps to bring a cost-effective solution without the need of whole changing whole system. It provides extra security to current infrastructure without the need for a complete overhaul, making it a good choice for various security setups. © 2024 IEEE.

关键词： Object recognition

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A Noval Text To Speech Conversion Using Hierarchical Neural Network

A Noval Text To Speech Conversion Using Hierarchical Neural ...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Yuvega, S. Rajendran, P. Selvi Hindustan Institute Of Technology And Sciences Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364828

The creation of a realistic voice from written text is revolutionized by the state-of-the-art paradigm in text-to-speech (TTS) systems, the Hierarchical Neural Network Architecture (HNNA). An extensive analysis of the important role the HNNA plays in identifying hierarchical patterns in textual input a function that enables the generation of expressive and contextually relevant speech is done in this abstract. The HNNA captures language hierarchies via hierarchical representations. It starts with word embedding analysis of textual inputs and moves on to sentence and document abstractions. Modern models like RNN are used in this architecture to generate high-quality speech signals, and transformer-based encoders decode hierarchical text representations. The integration of linguistic patterns and emphasis on context-aware processing make the HNNA noteworthy. Because of this, speech produced by contemporary TTS systems can sound more intonated, realistic, and understandable. © 2024 IEEE.

关键词： Network architecture

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Fabrication and control of magnetic planar nanorobots 5

Fabrication and control of magnetic planar nanorobots

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5th international conference on Control, robotics, and Intelligent System, CCRIS 2024

作者： Li, Zerui Jiang, Teng Li, Dongrui Qin, Jiazheng Cheang, UKei Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

With the development of science and technology, cross-scale robots are becoming increasingly popular. For different a pplication s cenarios, r obots w ith d iverse s cales a nd f unctions a re a lso r equired. M icron a nd n ano scale robots are typically used for targeted drug delivery or micro signal detection in the body. In order to enable micro and nano robots to enter the tissue through the finer b lood v essels i n t he b ody f or e fficient dru g delivery and other functions, it is required that the size of the robot is small and it can be controlled accurately. We here propose an achiral planar nanorobot construction capable of stable motion in the presence of a consistent rotating magnetic field. U sing n anoimprint t echnology, m agnetic n anorobots s maller t han o ne m icron a re manufactured in batches. The motion of the nanorobots is controled by Helmholtz coils which create a revolving magnetic field. T he p reparation a ccuracy, m oving s peed, m oving a ccuracy a nd b iocompatibility o f t he n anorobots were tested, and anti-cancer drugs were loaded on the surface of the nanorobots by means of surface modification, and the rate of drug release was subsequently evaluated. The fabrication process and magnetic control strategy of the nanorobots in this work helps the future investigations of the drug-carrying robots in body. © 2024 SPIE.

关键词： Nanorobots

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Unveiling Hidden Insights: Role of Data Analytics for Stakeholders in Modern Energy Internet

Unveiling Hidden Insights: Role of Data Analytics for Stakeh...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Jeevanantham, Y. Alexander Sarupriya, S. Janane Peneti, Subhashini Shahnaz, K.V. Kaliappan, S. R.M.K. Engineering College Department of Cse Chennai India Velammal Engineering College Department of Ece Chennai India Kalasalingam Academy of Research and Education Department of Business Administration Virudhnagar India Mlr Institute of Technology Department of Csit Telangana India Sagunthala R & D Institute of Science and Technology Department of Ece Chennai India Lovely Professional University Division of Research and Development Jalandhar India

ISBN: (纸本)9798350388800

The Energy Internet has ushered in a new era of energy management with diverse energy sources, shifting client needs and environmental concerns. Data analytics helps everyone solve challenges and seize opportunities in today's unpredictable environment. This essay explores the complex world of data analytics and its importance for Energy Internet workers. This essay emphasizes the importance of data analytics for energy professionals. It combines Time Series Forecasting, Machine Learning for Anomaly Detection, and Predictive Analytics for Renewable Energy Integration to create a novel method. These algorithms form a data-driven system to tackle the energy industry's biggest difficulties. A comparative study was done to fully review the procedure. This research compares the recommended strategy to corporate standards and highlights its merits and downsides. The effectiveness of these approaches is measured by MAE, RMSE, F1-Score, Precision, and Recall. The analysis found that the recommended technique strikes a good compromise between accurate forecasts and outliers. It consistently improves energy demand prediction, system stability, and green energy utilization. This comprehensive approach empowers everyone to make data-driven decisions, ensuring the long-term viability and efficiency of the contemporary Energy Internet. © 2024 IEEE.

关键词： Analytics Data Energy Internet Management Methods Modern Performance Predictive Renewable Resilience Stakeholders Sustainability technology Time Series

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Real Time Monitoring and Configuration Interface for Smart Home Device Management Using Streamlit and Pygame

Real Time Monitoring and Configuration Interface for Smart H...

引用

2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Mani, G. Suma Krishna, G. Venkata Praveena, M.D. Anto Asha, P. Selvan, Mercy Paul Sathyabama Institute Of Science And Technology Dept. Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

One of the helpful tool for measuring and managing home power consumption is one of the clever and creative tool for tracking the usage of Home Power Management System. The Goal of this system is to lower the power bills, also promote energy efficiency, and provide the users active control over how much energy they use. Smart meters, an intuitive and user-friendly smartphone app, and real-time energy monitoring sensors are some of the system's essential parts and these are the key parts of the system. Installing smart meters makes it possible to accurately track the power usage and provide data to the system. Users can be able to see their energy usage instantly and make smart decisions when real-time energy monitoring equipment is included. Further, the system uses advanced smart technology, analytics and machine learning algorithms to provide clients customized suggestions on how to save energy consumption. Homes may save a lot of money on electricity bills, help the environment, and have more control over how much energy they use by using our Smart Home Power Management System. © 2024 IEEE.

关键词： Smart meters

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Multi-Attention Fusion Lightweight Single Object Tracking Algorithm 7

Multi-Attention Fusion Lightweight Single Object Tracking Al...

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7th international conference on robotics, Control and Automation engineering, RCAE 2024

作者： Bao, Juntao Zhao, Jixing Liu, Bingyou Zhang, Dongxiang Anhui Polytechnic University Dept. School of Electrical Engineering Wuhu China Huaneng Chaohu Power Generation Co. Ltd. Dept. R&d Department ChaoHu China Anhui Tianbing Electronic Technology Co. Ltd. Dept. R&d Department Wuhu China

ISBN: (纸本)9798350355642

With the continuous development of mobile application platforms, balancing real-time performance and accuracy has become a major challenge for object tracking technology, especially on resource-limited mobile devices. To address these challenges, a novel tracking algorithm called NanoMViT (Nano Mobile Vision Transformer for Object Tracking) and the ECSA (Efficient Channel and Spatial Attention) multi-attention module were proposed. By optimizing the backbone network architecture, the parameters of each module were significantly reduced. The final algorithm has a parameter count of only 709.134k and MACs of only 264.127M. Compared to the baseline algorithm, the parameter count is reduced by 66.3%, and the computational load is reduced by 50.2%. To validate the algorithm's performance, comprehensive evaluations were conducted on multiple standard tracking datasets, including VOT2018, DTB70, and LaSOT. The results show that the algorithm outperforms the baseline in aspects such as rapid deformation, tracking of similar objects, and performance under complex lighting conditions. These findings demonstrate that the algorithm has high practicality and efficiency in mobile tracking applications, but further validation is required in more complex environments. © 2024 IEEE.

关键词： Prisms

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Code converter realization in IoT by TCP/IP network layer through node MCU and LabVIEW 5th

Code converter realization in IoT by TCP/IP network layer th...

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5th international conference on advances in AI for Biomedical Instrumentation, Electronics and Computing, ICABEC 2023

作者： Dhanabalan, G. Rajan, H.B. Michael Ashok, R. Department of CSE Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Avadi Chennai India Department of Mechanical Engineering Kings College of engineering Pudukkottai Punalkulam India Department of ECE Kamaraj College of Engineering and Technology K. Vellakulam India

ISBN: (纸本)9781032642987

Internet of Things (IoT) categorized into the fourth industrial revolution attracts researchers to realize different applications in IoT environment. Its architecture uses the existing network layers like TCP/IP, UDP, CoAP protocols. These protocols are tailormade to satisfy the requirements of IoT architecture. This work has used TCP/IP protocol to realize an IoT architecture using NodeMCU and LabVIEW. NodeMCU was configured to be the server and the LabVIEW was used to be the client which can access data from NodeMCU. NodeMCU is embedded with the Wi-Fi device. The configuration helped to realize IoT architecture through code convertor. NodeMCU receives the decimal number from the client, converts into binary and transfers it to the client. The client designed using LabVIEW displays the result. Security in data access is ensured as the NodeMCU will respond to the client only when it receives the keyword encoded by the designer. © 2024 The Author(s).

关键词： Internet of things

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Blockchain - Driven Health Record Storage and Disease Prediction Using Machine Learning

Blockchain - Driven Health Record Storage and Disease Predic...

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2024 international conference on advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Ramadayaal, G.K. Sneha, D. Thanesh Kumar, P. Vandhana, J. Priya, V. Dr. N.G.P Institute Of Technology Department Of Computer Science And Engineering Coimbatore India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371567

The healthcare industry has been facing persistent challenges in managing patient health records, including transparency issues, data breaches, and inefficient data sharing across regional boundaries. In response to these challenges, an innovative application leveraging blockchain technology has been developed. This application ensures the global integrity, accessibility, and privacy of patient data by utilizing blockchain as an incorruptible digital ledger. Patient health details are securely stored, making them immune to tampering or theft, guaranteeing data security and confidentiality. Additionally, the application allows verified healthcare professionals worldwide to access patient information seamlessly, eliminating geographical boundaries. The integration of machine learning further enhances predictive capabilities, enabling personalized and proactive medical interventions. This innovative system represents a significant advancement in healthcare management, promoting accessibility, security, and predictive capabilities for improved patient care globally. With robust security metrics such as accuracy, false acceptance rate, false rejection rate, recognition rate and time for recognition in place, the application provides a secure platform for the exchange of patient data and predicts diseases. Compared to state-of-the-art approaches, our approach outperforms with good results and performance. © 2024 IEEE.

关键词： Blockchain

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