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Enhancing Communication through Speech to Sign Language Converter 2

Enhancing Communication through Speech to Sign Language Conv...

引用

2nd IEEE North Karnataka Subsection Flagship International Conference, NKCon 2023

作者： Gayana, M.N. Rumaiz, Mohammed Hussain, Shaz Rasheed Shravya, A. Acharya, Shreenath Parveen, Sana Systems St Joseph Engineering College Dept. of Intelligent Computing & Business Mangaluru India St Joseph Engineering College Dept. of Computer Science and Engineering Mangaluru India

ISBN: (纸本)9798350314045

There are millions of people suffering from speaking and hearing disabilities. Sign language is the only way to communicate for such people to convey their message. The advancement in technology has highly impacted this section of society, hence there is a need to deal with them. This paper describes the Application, "Speech to Sign Language Converter"for communicating with people having hearing and speaking impairments. The primary function of the Application is to convert input sentences into Indian Sign Language (ISL) actions in real time. It takes input in the form of speech or text and produces corresponding sign language using an Avatar which acts based on SiGML code. It can also be used to convert PDF based texts into sign language. In addition, the users can learn Indian Sign Language (ISL) using the tutorials provided within it. The application focuses mainly on converting local languages such as Kannada into ISL. © 2023 IEEE.

关键词： Audition

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Dynamic Image Deblurring based on Crosshatch Attention Adversarial Network and Hybrid Loss 5

Dynamic Image Deblurring based on Crosshatch Attention Adver...

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5th International Conference on Advancements in Computational Sciences, ICACS 2024

作者： Aslam, Ummama Shaukat, Arslan Azam, Basim Dept. of Computer and Software Engineering H-12 Islamabad Pakistan Institute of Integrated and Intelligent Systems Griffith University Brisbane Australia

ISBN: (纸本)9798350394764

Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwanted artifact that appears in the deblurred image. To tackle this problem an end-to-end approach is proposed for the recovery of sharp image from blurred one without the estimation of blur kernel. A special type of attention module known as crosshatch attention is used after Residual Block of Generator model for removing noise and for the collection of correlation of different pixels in an image. Hybrid Loss function is defined which focus on different part of image and improve edges and texture details. The performance of the model for deblurring is measured on GoPro dataset. Our proposed model has slightly higher objective and subjective evaluation i-e PSNR, SSIM value and the visual results. © 2024 IEEE.

关键词： Pixels

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Performance Improvement of Joint Space Distance Measurement for PIP joints 7

Performance Improvement of Joint Space Distance Measurement ...

引用

7th International Conference on Imaging, Signal Processing and Communications, ICISPC 2023

作者： Suzuki, Moeko Goto, Tomio Nagoya Institute of Technology Dept. of Creative Engineering Program Nagoya Japan Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan

ISBN: (纸本)9798350325072

In order to analyze progresses of rheumatoid arthritis, we are developing an application to measure the distance between finger joints from X-ray images. In this paper, we focus on second joints, which are known to be prone to arthritis. We have proposed a method of filtering images and detecting edges, which has improved accuracy. Experimental results show that practical application of this system will reduce the burden on physicians and contribute to early detection of rheumatoid arthritis. © 2023 IEEE.

关键词： Diseases

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Online Learning and Assessment of Theoretical Knowledge in Electrical engineering Courses for Part-Time Education 15

Online Learning and Assessment of Theoretical Knowledge in E...

引用

2023 15th Electrical engineering Faculty Conference, BulEF 2023

作者： Ivanova, Yoana Filipova-Petrakieva, Simona Technical University of Sofia Dept. Computer Systems Sofia Bulgaria Technical University of Sofia Dept. Fundamentals of Electrical Engineering Sofia Bulgaria

ISBN: (纸本)9798350326536

Nowadays our normal life is unavailable without the Internet. Through the web, the same information is accessed from different places in the world. Both desktop computers and various types of mobile devices, including phones, can be used. Recently, e-learning as a model for knowledge learning has become more popular. This became a necessity after the global COVID pandemic. In some aspects, online learning is even more effective than in person learning as it allows students to study at their own speed. In the present paper, a Web-based application for learning theoretical knowledge in a science subject field is developed. Lectures and sample quiz questions to assess the knowledge are implemented therein. In case of an incorrect answer to the test questions, the application refers the learner to the place in the theory corresponding to the question. Two roles are implemented in the application - administrator and user (learner). The following technologies - HTML, CSS, JavaScript, ***, MongoDB, Bootstrap, jQuery И PUG, are used to develop the application. Desktop and mobile versions of the application are proposed. It is directed only at learning and testing theoretical knowledge, in particular in the different courses in the field of Electrical engineering. It can be used to simplify some of the part-time learning education for students (lectures, tutorials, course assessments, and projects). The respective labs will be performed on-site - in laboratories. The final assessment of the studied subject can also be done online. It will save transportation time for both learners and teachers. And, time is money. © 2023 IEEE.

关键词： Students

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Effect of climatological variations on Eco-efficiency of Wastewater Treatment Plants operation 28

Effect of climatological variations on Eco-efficiency of Was...

引用

28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Revollar, Silvana Meneses, Montse Francico, Mario Vega, Pastora Vilanova, Ramon University of Salamanca Dept. Computer Science and Automation Salamanca Spain Universitat Autonoma Barcelona Dept. Telecommunications and Systems Engineering Barcelona Spain

ISBN: (纸本)9798350339918

This study addresses the effect of climate conditions on treatment effectiveness and energy consumption in a conventional Wastewater Treatment Plant (WWTP). It has been observed that winter temperatures below 12°C produce a deterioration of pollutants elimination and energy efficiency in the activated sludge process (ASP). Then, in this work, variations of climatological conditions are considered, and ASP control parameters are modified, to evaluate their effect into the eco-efficiency of the WWTP operation. The eco-efficiency of the operation is analyzed from a plant-wide perspective considering the effects on different units of the plant. The Benchmark Simulation Model 2 (BSM2), that represents a typical WWTP, is selected for simulations. Introduction of seasonal temperature effects on ASP control strategy are contemplated for future work. © 2023 IEEE.

关键词： Process control

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Device Identification using Network Traces in a Smart Home IoT Network 17

Device Identification using Network Traces in a Smart Home I...

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17th IEEE International Conference on Advanced Networks and Telecommunications systems, ANTS 2023

作者： Brahma, Jwngfu Matam, Rakesh Choudhury, Nikumani Indian Institute of Information Technology Dept. of Computer Science & Engineering Guwahati India Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Hyderabad India

ISBN: (纸本)9798350307672

Device identification is a crucial aspect of securing networks, particularly in the context of the Internet of Things (IoT), where a vast variety of devices are interconnected. Recently, there has been significant research on developing techniques for identifying IoT devices based on their unique characteristics, called as device fingerprints. These techniques use machine learning algorithms, which can effectively learn and classify devices based on their features. However, device identification remains a challenging task due to the diversity of IoT devices and the constant evolution of their characteristics. This paper presents our attempt at device identification by analyzing distinct device characteristics observed during network communication and using different machine learning techniques. © 2023 IEEE.

关键词： Internet of things

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Design and Evaluation of a Low-profile Haptic Interface Based on Surface Electrical Nerve Stimulation 1

Design and Evaluation of a Low-profile Haptic Interface Base...

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1st IEEE Conference on Telepresence, Telepresence 2024

作者： Jakes, Rachel S. Mesias, Luis Santos, Veronica J. Fu, Michael J. Tyler, Dustin J. Cwru Dept. of Biomedical Engineering United States Dept. of Mechanical and Aerospace Engineering United States United States Cwru Dept. of Electrical Computer and Systems Engineering United States The MetroHealth System Dept. of Physical Medicine & Rehabilitation United States Advanced Platform Technology Center Dept. of Va Northeast Ohio Healthcare System United States

ISBN: (纸本)9798331528249

Haptic feedback in telepresence applications is vital for remote task performance and object manipulation. To maximize telepresence capabilities, haptic systems need to be integrated with immersive telepresence interfaces such as virtual reality, which offer benefits such as improved spatial awareness and operator mobility. Compatibility with the mobility of these systems and their built-in optical hand tracking require low-profile wearable interfaces. Further, for full functional benefits, haptic systems must be able to elicit spatially congruent sensation without impeding operator movement and physical object interactions. In this paper, we describe the design of a lightweight, compact, and adaptable surface electrical nerve stimulation-based haptic interface. We demonstrate its capacity to consistently generate spatially congruent sensation on the all five fingertips without occlusion, as well as its compatibility with headset-based optical hand tracking. © 2024 IEEE.

关键词： Haptic interfaces

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Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

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Synergizing Measurement Science and Artificial Intelligence in Smart Agriculture

Synergizing Measurement Science and Artificial Intelligence ...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Lamonaca, Francesco Carni, Domenico Luca University of Calabria Dept. of Computer Science Modelling Eletctronics and Systems Engineering Arcavacata di Rende Italy

ISBN: (纸本)9798350324457

This paper would provide a comprehensive review of the synergistic integration of measurement science and artificial intelligence (AI) in the realm of smart agriculture. As agriculture undergoes a transformative phase toward precision and data-driven practices, the paper explores the critical role of measurement science in providing accurate data, while AI processes and analyzes this data to facilitate intelligent decision-making in smart agricultural systems. © 2023 IEEE.

关键词： Artificial Intelligence Distributed Measurement System Measurement Smart Agriculture

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A Power Quality Event Classifier Based on Convolutional Neural Network

A Power Quality Event Classifier Based on Convolutional Neur...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Lamonaca, Francesco Carni, Domenico Luca University of Calabria Dept. of Computer Science Modelling Eletctronics and Systems Engineering Arcavacata di Rende Italy

ISBN: (纸本)9798350324457

This article introduces a novel and accurate automatic classifier for Power Signal (PS) alterations. The efficient detection and accurate classification represent crucial steps in developing an automatic power quality (PQ) measurement system, which has become essential in contemporary settings. The objective of this article is to enhance alteration classification accuracy. This is accomplished by combining the Hilbert-Huang transform (HHT) and convolutional neural network (CNN). The HHT is employed to extract PS features and is resilient to the non-stationarity introduced by alterations. Meanwhile, the CNN is adept.at extracting information from the bidimensional characteristics of PS features and is robust against noise. Numerical tests demonstrate promising results showing high classification accuracy also in the case of PSs affected by high level of noise. © 2023 IEEE.

关键词： Classifier CNN Convolutional Neural Network Distributed Measurement systems Hilbert-Huang transform Measurement Measurement System Power Quality Power Signal

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