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Atrous Convolution-Based residual deep CNN for Image dehazing with Spider Monkey-Particle Swarm Optimization

Intelligent Automation & Soft Computing 2023年第8期37卷 1711-1728页

作者： CH.Mohan Sai Kumar r.S.Valarmathi Department of Electronics and Communication Engineering VelTech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

Image dehazing is a rapidly progressing research concept to enhance image contrast and resolution in computer vision *** to severe air dispersion,fog,and haze over the environment,hazy images pose specific challenges during information *** the advances in the learning theory,most of the learning-based techniques,in particular,deep neural networks are used for single-image *** existing approaches are extremely computationally complex,and the dehazed images are suffered from color distortion caused by the over-saturation and pseudo-shadow ***,the slow convergence rate during training and haze residual is the two demerits in the conventional image dehazing *** article proposes a new architecture“Atrous Convolution-based residual deep Convolutional Neural Network(CNN)”method with hybrid Spider Monkey-Particle Swarm Optimization for image *** large receptive field of atrous convolution extracts the global contextual *** swarm based hybrid optimization is designed for tuning the neural network parameters during *** experiments over the standard synthetic dataset images used in the proposed network recover clear output images free from distortion and halo *** is observed from the statistical analysis that Mean Square Error(MSE)decreases from 74.42 to 62.03 and Peak Signal to Noise ratio(PSNr)increases from 22.53 to *** proposed method with hybrid optimization algorithm demonstrates a superior convergence rate and is a more robust than the current state-of-the-art techniques.

关键词： Image dehazing computer vision convolutional neural network color distortion over-saturation pseudo-shadow phenomenon convergence rate

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Comparison of dL model for retinal diseases classification using OCT images 10

Comparison of DL model for retinal diseases classification u...

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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Madhumithaa, S. Masoodhu Banu, N.M. Jehosheba Margaret, M. Sarma, A. Padmanabha VelTech Rangarajan Dr Sagunthala R&D institute of science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350350951

Age-related macular degeneration (AMd) and diabetic macular edema (dME) affect the macula of the retina for the person above 50 years. Accurate diagnosis of eye diseases in the initial stages prevents blindness. Manual detection needs the use of trained human experts. Hence, automated models are necessary. In this research paper, a novel approach for detecting retinal conditions is proposed. This involves the progress of three deep convolutional neural network (CNNs) models viz., AlexNet, resNet50, and InceptionV3. These models are trained to classify Optical Coherence Tomography (OCT) retina images into three macular diseases viz., Choroidal neovascularization (CNV), dME, drUSEN, and Normal. The publicly available Kermany dataset is apply to test the accuracy of each model. The outcomes show that the AlexNet model achieves an accuracy of 97.2% followed by the InceptionV3 model (95%) and the resNet50 model (79.8%). This finding can help the Ophthalmologists for easy and fast diagnosis to ensure quality eye care for individuals who are at the risk of vision loss. © 2024 IEEE.

关键词： Optical tomography

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A Comprehensive review on the use of NPK Values in the detection of Tomato diseases 15

A Comprehensive Review on the use of NPK Values in the Detec...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Babu, Gurujukota ramesh Gokuldhev, M. Dept of CSE Veltech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Chennai India

ISBN: (纸本)9798331300579

diseases can kill tomato plants, diminishing productivity, and resilience. Thus, prompt and correct diagnosis is crucial for disease control. recently, automated tomato plant disease severity assessment methods have gained interest. We can identify tomato plant illnesses using value analysis. NPK measures soil nutrients for plant growth: nitrogen, phosphorus, and potassium. The immune systems and health of tomato plants depend on these nutrients. This paper reviews tomato plant NPK-based disease detection literature. This paper examines NPK-based tomato disease prediction studies and emphasizes nutritional balance for plant health and disease prevention. The introduction describes how automated NPK value-based systems and early tomato disease diagnostics are becoming more popular on to NPK levels, which affect plant health and disease resistance. This survey discusses nitrogen, phosphorus, and potassium. We discuss nutrient balance for plant health and disease control and how NPK values might forecast tomato illnesses. Nitrogen, phosphorus, and potassium's influence on plant health and disease resistance are thoroughly addressed. NPK ratios for tomato plant health maintenance are also covered. NPK data is used to test tomato sickness prediction systems. © Grenze Scientific Society, 2024.

关键词： Fruits

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Virtual Car Showroom 15

Virtual Car Showroom

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Malarvizhi, N. Karthikeyan, V. Kumar, Abhay raj, Nirmal Kumar, Abhishek VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of CSE Chennai India

ISBN: (纸本)9798331300579

A virtual showroom is a digital representation of a physical showroom or store, where customers can browse and interact with products in a virtual environment. This can include features such as product information, 360-degree views, and the ability to zoom in on products for closer inspection. The showroom will allow users to explore and interact with different car models in a 3d environment, providing a realistic and immersive experience. Some examples of companies that use virtual showrooms include BMW and ralph. The comfort of real-world experience at their fingertips without the need of travel. The virtual showroom will include interactive features that allow users to interact with the car models. This will require programming using C# scripting in Unity, including animations, physics simulations, and user input handling. The car models will also be programmed with interactive features, such as opening doors, adjusting seats, and turning on headlights. © Grenze Scientific Society, 2024.

关键词： Helmet mounted displays

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Automated Breast Cancer diagnosis Using deep Learning CNN Models 2

Automated Breast Cancer Diagnosis Using Deep Learning CNN Mo...

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2nd IEEE International Conference on Emerging research in Computational science, ICErCS 2024

作者： Saravanan, G. Jeevanantham Prabin, S.M. Parthasarathy, r. VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Design Chennai India

ISBN: (纸本)9798331534950

The study introduces a deep learning model, CCNN, developed to identify and classify eight types of breast cancer: normal adenosis, normal fibroadenoma, normal phyllodes tumor, normal tubular adenoma, malignant ductal carcinoma, malignant lobular carcinoma, malignant mucinous carcinoma, and malignant papillary carcinoma. This model was integrated with five pre-existing models - Xception, InceptionV3, VGG19, MobileNetV2, and resNet101 - all trained for image classification using the ImageNet database, to categorize breast cancer MrI images. The dataset, sourced from Kaggle's repository, was further augmented using the Generative Adversarial Network (GAN) technique. For 30 experiments carried out to evaluate the introduced model and the transfer learning of five and proposed CCNN models, the F1-score values accuracy yielded were respectively: 98.04%, 96.13%, 98.54%, 97.11%, 94.20% and 98.98%. This study emphasizes the importance of improving the accuracy of early breast cancer detection to enhance the survival rates of patients. © 2024 IEEE.

关键词： Generative adversarial networks

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Simulational Study for designing Lung on-Chip 10

Simulational Study for Designing Lung on-Chip

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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Perumal, d. Jha, Sweta Beeta, Thiyam deepa Ghimire, Smriti Shelishiyah, r. Veltech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350350951

The organ-on-chip (OOC) platform enables faster, better, and less expensive drug development, disease modeling, customized treatment, and insights into human health by providing flexibility and robustness in drug testing. Animal models, on the other hand, have failed to provide effective and efficient drug testing results since different species have distinct characteristics. Here, this study reports a lung-on-chip (LOC) aiming to mimic the basic physiological response invitro human lungs while breathing. This microfluidic device performed the mechanical movement of 3d cyclic stretching inspired by breathing movements. This device consisted of 2 parts, the fluidic, and pneumatic parts. This proposed microfluidic chip had two methods of operating, one was breathing mode and another one was medium exchange mode. The simulation of the lung-on-chip was done in Ansys workbench by using static structural and Computational Fluid dynamics (CFd). The proposed microfluidic chip has great potential for drug testing and new drug development and has a wide range of applications. © 2024 IEEE.

关键词： Microfluidic chips

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Structured Approaches to Fostering robustness in Engineering of Systems for the digital domain 15

Structured Approaches to Fostering Robustness in Engineering...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： ravula, deepak VelTech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Department of ECE Chennai India

ISBN: (纸本)9798350370249

Crafted under the umbrella of the dArPA Cyber Assured Systems Engineering (CASE) initiative, BriefCASE emerges as an open-source model-centric engineering environment designed to shape cyber-resilient system blueprints. Its arsenal of instruments generates meticulous substantiation upheld by the framework. This evidence compilation serves as the foundation for substantiating assurance claims. This paper outlines a hierarchical pattern taxonomy tailored to attain cyberresilience assurance, seamlessly instantiated by briefCASE throughout system development. The amassed evidence corpus within the framework undergoes automated evaluation within the ensuing assurance discourse, confirming the fulfillment of cyberresilience goals. © 2024 IEEE.

关键词： Open source software

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Maximizing Privacy on Social Media through the Safer Tweets Strategy 15

Maximizing Privacy on Social Media through the Safer Tweets ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： ravula, deepak VelTech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai Avadi India

ISBN: (纸本)9798350370249

In an era of pervasive digital connectivity, concerns about privacy on social media platforms have become increasingly prevalent. The 'Safer Tweets' strategy offers a comprehensive approach to maximizing privacy and security while engaging on social media platforms, particularly Twitter. This strategy encompasses a combination of proactive privacy settings adjustments, mindful sharing practices, and awareness of potential risks. By implementing the Safer Tweets strategy, users can better protect their personal information, mitigate the impact of data breaches, and maintain greater control over their online presence, ultimately fostering a safer and more secure social media experience. © 2024 IEEE.

关键词： Privacy Privacy settings Safer Tweets Strategy Social media Twitter Using two-factor authentication (2FA)

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driving Aid Utilizing Android Application

Driving Aid Utilizing Android Application

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2023 Innovations in Power and Advanced Computing Technologies, i-PACT 2023

作者： Gomathi, N. Maddipatla, Sujitha Yadavakunta, Nisha Sree, Gali Teja Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350325188

Now-a-days, Transportation is the most important necessity for the people. So, the means of transport is increasing severely. In consequence, there is an extreme raise in road accidents. Automobile companies are hardly trying to overcome these issues and improved many Smart Conveyance Systems. Finding accidents and location of Vehicles with these in-built smart systems and sensors is easy. The detection of accident through the sensors is easy. But there are many drawbacks through this, like many vehicles cannot hold the hardware components and is high-priced to set up. In spite of these sensors, accident exposure can be done with the Internet of Things (IoT). The main aim of this system is to offer the driving assistance with low cost using the mobiles and its multifarious features. To assist the driver with respect to the simultaneous environment & surroundings an android application is developed. [1]To observe the surroundings LidAr is used and, Accelerometer is used to check speed, noise and pressure values of the vehicle. Information attained by the LidAr and Accelerometer is then analyzed to identify the possibility of accident. A caution message will be sent to the driver, rescue team, and family members through the navigation system.[4]. © 2023 IEEE.

关键词： Accident detection Internet of Things Smart conveyance Systems

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A Smart Healthcare Application for Early Heart disease Prediction: Leveraging Feature Optimization and deep Learning Techniques 2

A Smart Healthcare Application for Early Heart Disease Predi...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Manivannan, d. Manikandan, N.K. Sathiya Priya, S. Bharathi, S. VelTech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Chennai600062 India

ISBN: (纸本)9798350368413

Internet of Things (IoT) and Information technology (IT) are integrated and released as many browser-based applications that can fulfil the needs of people in this smart world. Especially, these technologies are used in medical field widely to provide the rich medical facilities and services to the society. Even though, the society is not fulfilled in the medical facility due to the lack of awareness and fast services. So that the people are trailing their living days every day. This is the right time to enrich the medical facilities by providing rich facility and services through available technologies. This paper suggests a novel smart healthcare system that employs feature optimization and an ensemble deep classifier to forecast illnesses, including heart disease, cancer, and diabetes, as a result of its perseverance. The optimization technique random Search Algorithm (rSA) was used in this study to identify the most impactful features for improving the prediction accuracy. A new ensemble deep classifier was also developed to effectively diagnose diseases. The classifier was created by combining the rSA base Fuzzy decision Tree Algorithm (rFdTA) with the Convolutional Neural Network (CNN). The system's performance was evaluated through various experiments and found to be both efficient and effective, outperforming existing healthcare systems. © 2024 IEEE.

关键词： Convolutional neural networks

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