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Performance Analysis of Vision Transformer Based Architecture for Cursive Handwritten Text Recognition 26

Performance Analysis of Vision Transformer Based Architectur...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Chowdhury, Avishek Hossen, Md. Ahasan Hasan, Mohammad Rukunuddin Osmani, Sheikh Md Premier University Dept. of Computer Science & Engineering Chattogram Bangladesh

ISBN: (纸本)9798350359015

computers have been given vision by researchers across the world for many years. Now it is the era of digitization. Recognizing handwritten text is a must for a computer vision system. Due to the variation and complexity of the cursive writing style, the holistic approach is mostly used for the recognition of cursive scripts. Though Convolutional Neural Network (CNN) based models have been employed in literature for Holistic Handwritten Text Recognition (HTR) of different domains, recent breakthroughs in the image classification Vision Transformer (ViT) based models have not been utilized for HTR so far. In this research, we have designed a ViT-based model for the HTR of various cursive scripts. To validate the performance of the model, various handwritten datasets of cursive scripts have been used. The notable finding includes that the accuracy of the designed model has increased by up to 26% after applying the image data augmentation techniques. © 2023 IEEE.

关键词： Augmentation Cursive Handwritten Text Recognition (HTR) Vision Transformer

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Blockchain Unleashed: Exploring its Multifaceted Applications and the Dynamics of Proof-of-Work

Blockchain Unleashed: Exploring its Multifaceted Application...

引用

2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Hassan, Inzimam Ul Ahmad Lone, Zeeshan Kaur, Inderdeep Kaur, Gaganjot Siya, Siya Priya, Simran Chandigarh University Dept. of Computer Science and Engineering Mohali India Vivekananda Global University Dept. of Computer Science and Engineering Jaipur India Chandigarh University Dept. of Cse Mohali India

ISBN: (纸本)9798350308167

In a range of sectors, such as banking, healthcare, and the Internet of Things, we have seen several data security and confidentiality issues. So, it is revealed that blockchain can provide a solution to the security problem. Thanks to the distributed database technology known as a blockchain, a trusted third party are not required for secure and transparent transactions between parties. The integrity of the chain is ensured by the cryptographic hash of each block in the chain, which makes each one tamper-proof. Blockchain technology has the potential to revolutionize a wide range of industries, from finance to healthcare, by providing a secure, efficient, and transparent method of storing and transmitting data and value. After reading the research on blockchain applications in different fields, we will highlight some of the major advantages we understand © 2023 IEEE.

关键词： banking finance Blockchain security integrity tamper-proof

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Learning to Communicate Using Action Probabilities for Multi-Agent Cooperation

Learning to Communicate Using Action Probabilities for Multi...

引用

2023 IEEE International Conference on Agents, ICA 2023

作者： Bai, Yidong Sugawara, Toshiharu Waseda University Dept. Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350312782

While communication is an essential tool for cooperation in multi-agent systems (MAS), existing approaches generally assume high-dimensional messages genereated by deep networks, which are uninterpretable for humans and require expensive transmission and complex encoding/decoding networks in agents. Uninterpretability may in turn raise reliability and security issues for the systems. To achieve low-dimensional and interpretable communication, we demonstrate that each agent's action probabilities can be used as messages, inspired by the fact that humans often share likely actions during collaboration. Our proposed method, communication based on action probabilities (CAP), is a simple yet effective communication architecture for coordination and collaboration in MAS, which facilitates our understanding of the agents' learned coordinated and cooperative behaviors. Moreover, because messages can be generated by the actor network, which is usually implemented in deep reinforcement learning agents, we can eliminate the requirement of extra message-generator networks. Our experiments show that CAP can achieve comparable performance to those of the state-of-the-art methods, with quicker convergence, simpler network structures and better interpretability. © 2023 IEEE.

关键词： Reinforcement learning

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Lung Cancer Detection Using Machine Learning Methods

Lung Cancer Detection Using Machine Learning Methods

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2023 IEEE Asia-Pacific Conference on computer science and data engineering, CSDE 2023

作者： Arka, Dipak Debnath Tafhim, Sad Md. Anan, Rawnak Muntaha Rahat, Nusaibah Ishan, Samiu Mostafa Tanvir, Sifat Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350341072

Cancer-related death is now more common than ever with cancer of the lungs being the leading cause of it. In such regards, the survival percentage for individuals with lung cancer must be increased through early identification. In this paper, we propose a machine learning-based approach for lung cancer detection using data from patients. The proposed method has three stages: preprocessing, feature extraction, and classification. In preprocessing, we extracted the necessary data from the dataset we collected. In the feature extraction stage, we processed the raw data while keeping the original information unchanged, in order for the classifier to work on. Finally, in the classification stage, we use 6 different classifier models to classify the extracted features. We evaluated the proposed method on a publicly available dataset from Kaggle of lung cancer causes and age. The results of the trial confirm the feasibility of the suggested strategy to achieve high accuracy, sensitivity, specificity, and AUC score. In conclusion, using machine learning, The suggested approach offers a powerful and efficient way to detect lung cancer. The proposed method can potentially assist in the detection of lung cancer, thereby improving the survival rate of lung cancer patients. © 2023 IEEE.

关键词： Feature extraction

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Enhancing Biomedical Literature Analysis to Predict Drug Interactions Using Multi Criteria Decision Making and LSTM-CNN Model

Enhancing Biomedical Literature Analysis to Predict Drug Int...

引用

2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Sankaran, A. Sathiyamurthy, K. Puducherry Technological University Dept. of Computer Science and Engineering India Puducherry Technological University Faculty of Computer Science and Engineering India

ISBN: (纸本)9798350315127

The extraction of information from unstructured text has become a crucial task in the biomedical literature field. Specifically, the analysis of various relationships such as Drug Food, Drug Disease, Drug non-prescription and Drug Drug interactions has gained significant importance. To accomplish this, a combination of Multi Criteria Decision Making (MCDM) and machine learning techniques has been employed. A dataset has been curated and utilized to train a model based on Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN). The trained model enables accurate predictions and identification of relevant information pertaining to drug interactions in biomedical literature. This approach enhances the understanding and knowledge extraction from vast amounts of unstructured text data, leading to improved insights and potential advancements in the field of biomedical research. © 2023 IEEE.

关键词： Long short-term memory

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2D/3D Echocardiography Frame Rate Enhancement by Means of a Novel Spatio-Temporal Reconstruction Technique

2D/3D Echocardiography Frame Rate Enhancement by Means of a ...

引用

2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Afrakhteh, Sajjad Iacca, Giovanni Demi, Libertario University of Trento Dept. of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350346459

Frame rate, i.e., the number of frames displayed per second, is a crucial aspect in ultrasound imaging. Increasing the frame rate is required in echocardiography because it helps clinicians assess faster heart movements, especially in the valves. Higher frame rates are needed to capture the mechanical characteristics or transitory events of the heart, especially in 3-dimensional (3D) echocardiography. The main objective of this study is to propose a solution for increasing the frame rate of 2D/3D echocardiography. To this end, we propose a post-processing technique based on a novel 2D spatio-temporal interpolation to increase the frame rate. We utilize radial basis functions (RBF) to perform the interpolation. More precisely, we propose a novel intensity variation time surface (IVTS) approach to integrate both temporal and spatial information into the reconstruction. We apply the proposed technique to 2D and 3D echocardiography datasets at the radio frequency (RF) level of the post-processing stage for different down-sampling (DS) rates. The results demonstrate that we can increase the frame rate of 2D/3D echocardiography by a factor 4 while preserving a structural similarity (SSIM) index greater than 0.96 and 0.87, respectively for 2D and 3D imaging. © 2023 IEEE.

关键词： Interpolation

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Empathy-Aware Behavior Trees for Social Care Decision Systems

Empathy-Aware Behavior Trees for Social Care Decision System...

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2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023

作者： Dell'Acqua, Pierangelo Costantini, Stefania Dyoub, Abeer Gasperis, Giovanni De Monaldini, Andrea Rafanelli, Andrea Dept. of Science and Technology Linkoping University Norrkoping60351 Sweden Dept. of Information Science and Engineering and Mathematics University of Aquila L'Aquila67100 Italy Dept. of Computer Science University of Pisa Pisa56100 Italy

There is growing attention on the importance of building intelligent systems where humans and Artificial Intelligence-based systems (AIs) form teams exploiting the potentially synergistic relationships between humans and automation. In the last decade, the computational modeling of empathy has gained increasing attention. Empowering interactive agents with empathic capabilities leads, on the human's side, to more trust, increases engagement, and thus interaction length, helps cope with stress. These findings suggest that agents endowed with empathy may enhance social interaction in educational applications, artificial companions, medical assistants, and gaming applications. This article focuses on modeling the empathic behavior of virtual agents interacting with humans. We propose a formal model that enables virtual agents to exhibit empathic, emotional behavior. Specifically, we extend the modeling of empathy via behavior trees with a new type of node allowing the specification of various kinds of empathy. Using the proposed extension, we show how different agents' reactive behavior can be modeled. © 2024 The Author(s). Published by Elsevier B.V.

关键词： Intelligent systems

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Optimal IPL Playing 11 Team Selection 8

Optimal IPL Playing 11 Team Selection

引用

8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Ravichandran, Nilesh Nihal Chengappa, P.A. Rao Rebala, Pranav PES University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350334012

Since the inception of the Indian Premier League (IPL), the demand for quality data analysts has increased. The task to pick an ideal playing 11 from a huge squad is a real challenge and picking the best team can greatly improve a team's chances of winning. This project aims to predict the best possible playing 11 from a given set of players taking into consideration a number of factors like runs scored, runs conceded, strike rate, dot balls bowled etc. and this is essential as it can help pick an optimal eleven. Not only are the best batsmen and bowlers predicted but also the all-rounders which give a real balance to the team. Three models have been tested- XGBoost, Linear Regression and Random Forest. Linear Regression yields better results since it gives the least RMSE value. © 2023 IEEE.

关键词： Linear regression

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Efficient Support System for Hearing Disabled using CNN 5

Efficient Support System for Hearing Disabled using CNN

引用

5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Sharma, Mayank Goswami, Puneet Srm University Dept. Of Computer Science And Engineering Delhi India

ISBN: (纸本)9798350330861

Objective: In today's world communication plays a major role in a person's life in many ways. Communication is a process of conveying or transferring your feelings, knowledge or ideas to the rest of the world. This becomes very difficult for a person who cannot speak or listen. To overcome this problem we aim to develop a sign language system that is able to detect the hand gestures of the Deaf and Dumb from the captured images and convert them into a text format so that a person who does not have any knowledge of the sign language can understand them easily. Scope: This project aims at detecting the hand gestures performed by the deaf and dumb person and translate those signs into readable form so that the communication barrier between the physically challenged and ordinary people can be removed. Method: Deep learning and computer vision for detecting the signs of the sign language performed by the deaf and dumb people have proved to be very efficient. The dataset contains images of different signs in the Indian sign language which is used to train a neural network. Convolutional Neural Network (CNN) is used for the classification of the signs for the alphabet and numbers. Findings: This research has immense capability to detect the hand gestures performed by Deaf and Dumb people and to remove the communication gap between deaf and dumb people and the ordinary people. Therefore, our paper will provide a convenient way for ordinary people to understand and easily understand the deaf and dumb people. © 2023 IEEE.

关键词： computer vision

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A Time-varying Velocity Control Strategy for Balancing Exploration and Exploitation Behaviour of a Binary PSO

A Time-varying Velocity Control Strategy for Balancing Explo...

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2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Siddique, Md. Abu Bakkar Islam, Md. Jakirul DUET Gazipur Dept. of Computer Science and Engineering Gazipur Bangladesh

ISBN: (纸本)9798350316001

Combinatorial optimization problems (COPs) are NP-hard, and their solution space is discrete, which poses a significant challenge for optimization algorithms. Binary Particle Swarm Optimization (BPSO) is wel-known optimization technique that has been widely applied in various type of COPs. However, one of the challenges in BPSO is to balance exploration and exploitation to locate the optimal solution. This paper presents a Time-varying Velocity Control (TVC) strategy to balance exploration and exploitation in a BPSO. The TVC strategy utilizes a time-varying control parameter to adjust the velocity of the particles, allowing for more exploration in the early phases of the optimization process and more exploitation as the search progresses. The proposed strategy is evaluated on a set of benchmark combinatorial optimization problems, and the results demonstrate that it outperforms other commonly used BPSO strategies in terms of both efficiency and solution quality. Furthermore, the TVC strategy is shown to be robust to changes in the problem landscape, making it a promising approach that can be used for solving a wide range of combinatorial optimization problems. © 2023 IEEE.

关键词： Combinatorial optimization

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