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Indian Sign Language Recognition Using Video vision Transformer

Indian Sign Language Recognition Using Video Vision Transfor...

引用

Advancement in Technology (ICONAT), international conference for

作者： Ojaswee R Sreemathy Mousami Turuk Jayashree Jagdale Mohammad Anish Department of E&TC Engineering Pune Institute of Computer Technology Pune India Department of Information Technology Pune Institute of Computer Technology Pune India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

Sign language is a way of communication that uses hand shapes, orientation, movements, and facial expressions to express instead of spoken words like normal language. Different regions have developed their own versions of sign language. In India, Indian sign language (ISL) is the primary mode of communication for more than 5 million speech or hearing impaired people. However, the knowledge of signing and understanding the ISL is only limited to the deaf community, which can make it hard to communicate with the people who don’t understand the language. Thus, effective recognition of ISL gestures is vital for seamless interaction between these impaired people and the broader society. The rise of artificial intelligence and computer vision models has provided us with many effective tools to tackle this challenge. While there has been some progress in this field, most research has focused on static signs or American Sign Language, leaving video-based recognition for ISL largely unexplored. To bridge this gap, our paper proposes an approach that utilizes Video vision Transformer (ViViT) architecture for ISL recognition. We have experimented with different layers and different numbers of attention heads to get a model that works best for the assigned task. Our architecture gives an overall accuracy of $\mathbf{9 6. 6 9 \%}$ and a top-5 accuracy of $\mathbf{9 9. 5 5 \%}$ on the sign recognition task using our own created VISL-PICT dataset.

关键词： Sign language computer vision Accuracy Shape Computational modeling Speech recognition computer architecture Streaming media Assistive technologies Transformers

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vision-Based Measurement Method for Internal Riveting of the Joist

Vision-Based Measurement Method for Internal Riveting of the...

引用

Electronic Technology, Communication and Information (ICETCI), IEEE international conference on

作者： Zongzhe Ni Jianjun Yi Yihan Pan Xinke Zhang Shaobo Wang Fanxin Li Department of Mechanical Engineering East China University of Science and Technology Shanghai China

The requirement for industrial automation and quality control is the fundamental driver behind the visual examination of workpieces. Due to the vast number of workpieces, high level of complexity, and harsh production environment in traditional industrial production, manual inspection's efficiency and accuracy struggle to satisfy production standards. Automated vision inspection technology can partially address these issues. Through digital image processing and other technical methods, vision inspection technology can quickly and accurately identify and analyze features like workpiece size and shape, realizing automated quality control and production process control. In addition, workpiece vision inspection technology has grown in significance with the rise of Industry 4.0 and smart production. This paper's focus is the joist's rivet head, which must be measured for its diameter, height, circularity, and edge distance to assess whether the rivet is successfully assembled by confirming that the rivet head's dimensions are accurate. This paper suggests using Euclidean clustering to segment the point cloud surface and converting the extracted surface into an image for global threshold segmentation to extract edge information in an effort to overcome the challenges posed by the reflection and shadows on metal workpiece surfaces. This research suggests that the holes created by the blockage of light source irradiation on joist edges be filled by filling the pixel values. In this study, the riveted head's diameter is accurate to within 0.1 mm, its height is accurate to within 0.02 mm, and the edge distance is accurate to within 0.2 mm.

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A lightweight distributed processing computer system

A lightweight distributed processing computer system

引用

Electronic Technology, Communication and Information (ICETCI), IEEE international conference on

作者： Zhenpeng Xu Weiwei Li Jinyong Yin Department of Computer Jiangsu Automation Research Institute Lianyungang China

For the needs of real-time parallel processing of critical task and real-time state control in muti-node computing system, a lightweight distributed processing computer mechanism is designed for iterative computing type tasks based on theoretical techniques such as memory computing and distributed computing. Using the feature of distributed collaborative processing, the data is deployed to different nodes to reduce the burden of each node and. To support continuous computational iterations, temporary data for each computation is temporarily stored in memory to reduce the disk IO access time during the iteration. Before the start of the whole task, the transformation relationship between the saved data is defined by generating the run plan graph of this task. In addition to load balancing of processing nodes, a balanced scheduling mechanism of control nodes is introduced to monitor the operation status of each node in real time through load balancing and control the deployment of computation tasks. Tests show that the designed lightweight computing mechanism outperforms the traditional distributed computing mechanism. In addition, the performance outperforms the mainstream memory-based distributed computing mechanism when carrying multiple tasks.

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Temperature control system of storage water heater based on self-learning 3

Temperature control system of storage water heater based on ...

引用

3rd IEEE international conference on Communications, Information System and computer Engineering, CISCE 2021

作者： Huang, Min Wu, Junqin Yang, Huanwen Zhong, Yiming School of Information Engineering Jiangxi University of Science and Technology Ganzhou China Guangdong Vanward New Electric Co. Ltd. Foshan China

ISBN: (纸本)9780738112152

To make the storage-type electric water heater work stably, a temperature control system with fast control speed and energy saving are designed and realized. The system uses CMS89F23x5B as the processor, and obtains the periodic sequence of daily water consumption by self-learning the user's daily hot water habits, and then uses a closed-loop negative feedback PID control structure to control the water temperature of the water heater. The results show that after the self-learning function is added to the system, the user's daily water consumption habits can be learned, and the final experimental measurement can save 22.5% of electricity, and verify the effectiveness of the identification method. © 2021 IEEE.

关键词： Three term control systems

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Facial Emotion Recognition and Detection Using Convolutional Neural Networks

Facial Emotion Recognition and Detection Using Convolutional...

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Smart Generation Computing, Communication and Networking (SMART GENCON), international conference on

作者： Renu Dalal Manju Khari Priyank Pandey Samanvay Jatana Vijay Joshi USAR Guru Gobind Singh Indraprastha University New Delhi India Department of Computer and Systems Science Jawaharlal Nehru University New Delhi India Department of Computer & Engineering Graphic Era Deemed to be University Dehradun Department of Information Technology Maharaja Surajmal Institute of Technology GGSIPU Delhi India

Facial emotion recognition is now becoming a hot topic in previous years as it helps in human computer interaction. As human emotions can be detected, there are various studies on it in the computer vision field. Humans can easily recognize the type of emotion from someone's facial expressions but it's tough for a computer machine. FER can be used in vast areas for applications such as education, social media, healthcare, Al based application, etc. In this research paper, the Convolutional Neural Network (CNN) technique has been built. The methodology is mainly divided into two steps: Haar cascade features from the face are extracted by using Viola Jones algorithm leading to facial identification and then facial emotion is recognised by using the help of neural network. This technique is built on conventional neural networks (CNN) and it has used FER2013 and CK+ dataset for detection of human emotions. This model consists of 3 completed connected layers and six convolutional layers. On the basis of our experimental results, this model has a validation accuracy of 68.26% with FER 2013 dataset and 91.58% with CK+ dataset.

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Neural Network Software to Process Medical Data Modeling 3

Neural Network Software to Process Medical Data Modeling

引用

3rd international conference on control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Emelyanov, Egor Polyakov, Maxim Volgograd State University Depart. of Information Systems and Computer Modeling Volgograd Russia

ISBN: (纸本)9781665439817

Microwave radiometry enables measuring the temperature in biological tissues at a depth of several centimeters. Temperature is a crucial source of data on person's physical condition. The paper is devoted to developing an approach to ensure early breast cancer diagnosis by mapping temperature using machine learning techniques, using convolutional neural networks in particular. The novelty of our approach lies in studying the images drawn up based on temperature data obtained from local measurement points, with different color schemes used. Interpolation algorithms were used to improve the quality of the images obtained. The originality of the approach lies in the fact that, in addition to measuring real patients, computer modeling of mammary gland thermal fields is also used. We found that the use of extremely-Accurate neural networks to diagnose breast cancers is an effective and viable approach. Even if few learning samples (192 examples) are available, our proposed algorithm shows roughly 80% high accuracy adjusted to the neural network topology and the color scheme applied. We also demonstrate the dependence of diagnosis quality on the number of source images used while training and testing. We have concluded that the combined use of the left and right mammary gland thermograms greatly improves diagnosis efficiency when using graphical image machine learning. © 2021 IEEE.

关键词： Diagnosis

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Enhanced Multiclassification of Avocado Leaf Diseases: CNN and Random Forest Integration

Enhanced Multiclassification of Avocado Leaf Diseases: CNN a...

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Innovation in Technology (INOCON), IEEE international conference for

作者： Taifa Ayoub Mir Sheifali Gupta Rahul Chauhan Mukesh Singh Deepak Banerjee Bura Vijay Kumar Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Dehradun Uttarakhand India Graphic Era Deemed to be University Dehradun Uttarakhand India School of Computer Science and Artificial Intelligence SR University Warangal India

Through the use of advanced machine learning techniques, the primary objective of this research is to develop and evaluate a classification model to identify a variety of illnesses that may affect avocado leaves. Despite exhibiting remarkable accuracy, recall, and F1-score metrics, the model displays good performance across a wide range of illness categories. The accuracy levels of the model, which range from 92.61% to 95.32%, are indicative of the effectiveness of the model in reliably detecting different kinds of diseases. Furthermore, recall rates, ranging between 91.53% and 94.44%, demonstrate the model's efficacy in collecting important cases within each illness categorization. The model demonstrates resilience in the classification of avocado leaf diseases, as it maintains an overall accuracy of roughly 93.66% during its operation. These results suggest that the model has the potential to facilitate early disease diagnosis and accurate identification, which would give major contributions to the enhancement of disease control systems in avocado farming.

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Automotive OTA Upgrade Scheme Based on Optimal Difference Algorithm

Automotive OTA Upgrade Scheme Based on Optimal Difference Al...

引用

Robotics, Automation and Intelligent control (ICRAIC), international conference on

作者： Guihe Qin Yingbei Wang Yanhua Liang Jiaru Song Changsha Automobile Innovation Research Institute Jilin University Changsha China College of Computer Science and Technology Jilin University Changchun China

In order to improve the efficiency and reliability of the automotive OTA (Over-the-Air) upgrade, and make it more adaptable to the characteristics of the car. In the paper, we propose to use an optimized BSDIFF algorithm to remotely swipe the car. Specifically, the divsufsort algorithm is used in the suffix sequence, and the Zstd algorithm is used in the compression and decompression process to further improve the upgrade speed. Fault-tolerance mechanism and buried point analysis mechanism are also designed to ensure the robustness of the upgrade process. We conducted OTA upgrade simulation experiment on Linux platform. Experiment results show that the proposed combinatorial optimization algorithm can improve the efficiency of ECU remote writing under the bandwidth limitation of vehicle network.

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Modular StoryGAN with Background and Theme Awareness for Story Visualization 3rd

Modular StoryGAN with Background and Theme Awareness for Sto...

引用

3rd international conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022

作者： Szűcs, Gábor Al-Shouha, Modafar Budapest University of Technology and Economics Műegyetem rkp. 3 Budapest1111 Hungary

ISBN: (纸本)9783031090363

Story visualization is a novel topic that intersects computer vision and natural language processing. In this task, given a series of natural language sentences that compose a story, a sequence of images should be generated that correspond to the sentences. Prior works have introduced recurrent generative models which outperform text-to-image models on this task;however, local and global consistency is a challenging attribute of these solutions. For the improvement, we proposed a new modular model architecture named Modular StoryGAN containing the best promising components of prior works. To measure the local and global consistency we introduced background and theme awareness, which are expected attributes of the solutions. Based on the human evaluation, the generated images demonstrate that Modular StoryGAN possesses background and theme awareness. Besides the subjective evaluation, the objective one also shows that our model outperforms the state-of-the-art CP-CSV and DuCo models. © 2022, Springer Nature Switzerland AG.

关键词： Visualization

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Automatic Temperature control System for the Firing of Bricks in the Company “Ladrillera el Toro S.A.C”

Automatic Temperature Control System for the Firing of Brick...

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computer, control and Robotics (ICCCR), international conference on

作者： Dana Garlet Arauco-Quispialaya Yuliana Milagros Matos-Cuadrado Gianella Ayline Quispe-Mallqui Herbert Antonio Vilchez-Baca Department of Industrial Engineering Universidad Continental Huancayo Peru Department of Industrial Enginnering Universidad Continental Huancayo Perú

The 18-hole King Kong bricks represent 55.8% of the material used in the construction of houses in Peru, the brick companies lack temperature controls since the OEFA paralyzed the brick activities due to excessive contamination in the firing stage. This work develops an automatic and manual temperature control system to improve production times in the company “Ladrillera El Toro S.A.C”. For the mechanical design, SolidWorks was used to place the entry gates of the bricks to the kiln, which inside the kiln thermocouples were installed to monitor temperatures in real time by programming blocks using TIA PORTAL connection adding a PLC S7-1200 1214 DC/DC/DC and a HMI TP700. Finally implementing the improvement proposal eliminated 1 day of assembly in artisan doors and has an adequate management of the required temperature of 950 degrees Celsius for the firing of the bricks having the manual and automatic option that allows to control the sawdust and chips once reached the temperature programmed by the operator, allowing to increase production and eliminating the bottlenecks of the company “Ladrillera El Toro S.A.C.”.

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