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A residual gated convolution summary generation model based on contrast learning 6

A residual gated convolution summary generation model based ...

引用

6th international conference on Electronic information technology and Computer Engineering, EITCE 2022

作者： Guan, Xiaohan Liang, Shuo School of Information Science and Technology North China University of Technology Beijing China

ISBN: (纸本)9781450397148

Contrastive learning achieves better results in several tasks in natural language processing. However, there are fewer studies on Chinese text summary generation tasks. In this paper, a new summary generation model is proposed. this model uses the reference summary of random word order as a negative sample. Let the model learn to predict the distribution of representations more reasonably. Using RoBERTa pre-trained language model to encode the text, the summary text is generated using the gated convolutional unit with the residual mechanism. the experimental results of the LCSTS dataset show that the model performs in this paper better than the baseline model. © 2022 Association for Computing Machinery.

关键词： Convolution

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A Multi-stage Feature Enhancement Network with Second-Attention for Image Captioning 6

A Multi-stage Feature Enhancement Network with Second-Attent...

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6th international conference on Artificial Intelligence and Pattern Recognition, AIPR 2023

作者： Yang, Xiaobao Yang, Yang Wu, Junsheng Ma, Sugang Hou, Zhiqiang Song, Bohui Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China School of Computer Science Northwestern Polytechnical University Xi'an710071 China

ISBN: (纸本)9798400707674

In the past few years, self-attention in Transformer has been widely used in natural language processing (NLP) and computer vision (CV) due to its excellent ability to capture global information, especially in image captioning, where the use of self-attention can significantly improve the representation of visual information. However, the obtained image feature from Transformer-based models suffers from two main problems, one is information redundancy due to the global aggregation of self-attention, and the other is the lack of semantic information caused by single-scale feature extraction. therefore, we first propose second-attention in this paper, by redistributing image attention weights, second-attention can effectively remove irrelevant information and enhance the attention to essential objects and relations. Meanwhile, to enrich semantic information and further enhance the role of second-attention, we design a Multi-stage Feature Enhancement (MFE) network to improve the ability to represent visual information. After conducting extensive experiments on the MS COCO dataset, we achieve significant improvements in all popular benchmarks, particularly BLEU4 increased by 1.6%, CIDEr increased by 3.4%. © 2023 ACM.

关键词： Semantics

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Use Case-Based Analytical Hierarchy Process Method for Software Requirements Prioritization 6

Use Case-Based Analytical Hierarchy Process Method for Softw...

引用

6th international conference on information technology, information Systems and Electrical Engineering, ICITISEE 2022

作者： Naufal Maulana, Moh. Zulfiqar Siahaan, Daniel Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia

ISBN: (纸本)9798350399615

there are many factors that can cause the failure of a software project. One of them is the failure to identify and address the problems stakeholders face due to ineffective requirements engineering. Another factor is the failure to correctly determine the priorities of software requirements. Due to limited resources of software projects, it is essential to focus on the most important requirements to ensure software success. therefore, requirement prioritization is a critical phase within the software development life cycle. this study proposes a method to prioritize software requirements based on the development of the Analytical Hierarchy Process (AHP) method. there are several limitations of the AHP method, namely suffering from scalability problems, time-consuming, and inconsistent due to the redundancy produced by the pairwise comparison. To address these limitations, we propose a method for requirements prioritization named the Use Case-Based Analytical Hierarchy Process (UC-Based-AHP), which aims to overcome the challenges faced by the AHP method by reducing the number of pairwise comparisons in the AHP method with the use of natural language processing (NLP) and previously created use cases. As a result, complexity will be reduced and the results obtained will have a 0.71 reliability value compared with the original AHP. © 2022 IEEE.

关键词： AHP Natural language processing Requirement Prioritization Software Requirements

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Automation using Artificial intelligence based Natural language processing 6

Automation using Artificial intelligence based Natural Langu...

引用

6th international conference on Computing Methodologies and Communication, ICCMC 2022

作者： Mohana, P. Muthuvinayagam, M. Umasankar, P. Muthumanickam, T. Government Polytechnic College Department of Electronics and Communication Engineering TamilNadu Dharmapuri India

ISBN: (纸本)9781665410281

In this proposed work, necessary design and optimized parameters are transmitted for the essential information exchange. this research study focuses on integrating WSN architecture. In actuality, many automated systems still require extensive human engagement;for example, a patient may need to visit multiple pharmacies in order to locate a specific sort of drug. A smart inventory system integrating Wireless Sensor Networks (WSN), Quick Response Codes (QR), and cloud services (web) would solve numerous difficulties while also saving money for both patients and stakeholders. With all these chores, a speedier and more reliable system is required to manage operational and repeatable processes. Recent advancements in the field of portable devices have been substantial, particularly in the area of audio/music information delivery systems such as headphones that link to mobile/portable devices via wired or wireless communication. Usage of headphones connected with mobile devices by all age group people is getting higher practically every day, for doing multiple businesses like navigation, automation, bill payment, contest participation, news and events social media. this paper suggests the usage of four typical home appliances: a fan, a light, a coffee machine, and door alarms, using a single remote. Natural language processing is used by the mobile device to interpret the user's voice command. To communicate with the Wi-Fi signals provided by these appliances, the project uses a smartphone application. the application gives commands to the Arduino devices and also responds to their responses. While a command is delivered from a remote location. As a result, the integrity and confidentiality of conveyed data, as well as the authentication of the services that provide that data are critical. As a result, security is a vital IoT feature. As a result, it includes a username and password-based authentication mechanism in the mobile application. To assist computers in understan

关键词： Automation

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Gesture Recognition based Fingertip Air Writing to Text Convertor using Image processing and HCI 8

Gesture Recognition based Fingertip Air Writing to Text Conv...

引用

8th international conference on advanced Computing and Communication Systems, ICACCS 2022

作者： Shanmugapriya, R. Magesh, G. College of Engineering Anna University Department of Information Science and Technology Guindy Chennai600025 India

ISBN: (纸本)9781665408165

Gesture Recognition based fingertip air writing to text converter which permits to write and sketch text characters in fore of a web camera in the laptop computer over the air. the two main tasks of proposed methods are a blue-colored object is taken in the hand. To perceive the written characters from video frames, a blue-colored object is being tracked and optical English text reformation is applied over the plotted images. Additionally, a stylus pen, touchscreen pen, keyboard, glove or any other device is not required for giving input characters a habitual human-computer interaction is developed to address it. Application based on Open CV with the python language is designed for experimental purposes. It is relevantly a straightforward software-based approach, which is effortless and effective. Moreover, it requires a web camera and a blue-colored object other than hardware or any other sensors. © 2022 IEEE.

关键词： Character recognition

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Sinhala Part of Speech Tagger using Deep Learning Techniques 6

Sinhala Part of Speech Tagger using Deep Learning Techniques

引用

6th IEEE international conference on Computational System and information technology for Sustainable Solutions, CSITSS 2022

作者： Sathsarani, M.W.A.R. thalawaththa, T.P.A.B. Galappaththi, N.K. Danthanarayana, J.N. Gamage, Anjalie Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9781665456982

Natural language processing (NLP) is a sub-field of Artificial Intelligence (AI) that consists of a collection of computational methods motivated by theory for the automated classification and reflection of human languages. the foundation for many sophisticated applications of NLP, including named entity recognition, sentiment analysis, machine translation, in-formation retrieval, and information processing, is laid by Part of Speech (POS) tagging, which is part of the lexical layer of NLP systems. In contrast to English, French, German, and other languages from the same geographical region, the development of high-accuracy, stable POS taggers for the Sinhala language is still in its early stages. Hence, Sinhala is identified as a low-resource language. the main objective of this research is to create a POS tagger for the Sinhala language to solve this issue. An innovative and novel strategy that has never been used with the Sinhala language has been designed. this approach has been suggested specifically to evaluate the possibility of enhancing the accuracy compared to other methodologies. So, deep learning algorithms have been applied in this study, which has a significant impact on improving tagger performance. First, highly accurate individual classifiers for primary POS tags were implemented, and then they were combined into one composite model. As expected, all individual classifiers and the final composite model have achieved a higher accuracy level. thus, it demonstrates that the proposed solution using deep learning algorithms outperformed other methods, such as rule-based and stochastic, in terms of accuracy. © 2022 IEEE.

关键词： Computational linguistics

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Detection and Classification of Cyberbullying in Social Media using Text Mining 6

Detection and Classification of Cyberbullying in Social Medi...

引用

6th international conference on Electronics, Communication and Aerospace technology, ICECA 2022

作者： Nisha, M. Jebathangam, J. Vistas Department of Computer Science Chennai India Vistas Department of Information Technology Chennai India

ISBN: (纸本)9781665482714

this research work intends to classify the texts associated with bullying contents in social media, especially twitter by using the text mining process. A Multi-Modal Detection and classification of Cyberbullying media is developed in the study. this model integrates textual, and metadata to identify the cyberbullying media in case of social networks. the process involves two phases training and test the cyberbullying data, where natural language processing (NLP) is applied as the pre-processing tool and then particle swarm optimisation is used as feature selection process. Finally, the study applies decision tree classifier to classify the instances associated with cyberbullying and after classification, these features are combined with text instances to detect the performance of the proposed model. the simulation is conducted to test the detection rate of the classifier than the existing methods. the results show that the proposed method achieves higher rate of classification and detection accuracy than the existing methods. © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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Optimizing Medical Image Report Generation with Varied Attention Mechanisms 6

Optimizing Medical Image Report Generation with Varied Atten...

引用

6th international conference on Contemporary Computing and Informatics, IC3I 2023

作者： Reddy, Pochamreddy Mukesh Verma, Vivek Kumar Chaitanya Varma, Mudunuri Venkata Manipal University Jaipur Computer and Communication Engineering Jaipur India Manipal University Jaipur Department of Information Technology Jaipur India Manipal University Jaipur Data Science and Engineering Jaipur India

ISBN: (纸本)9798350304480

Image captioning plays a crucial role in interpreting visual information in the medical field. this research paper represents an innovative approach to produce descriptive and insightful reports for its respective medical images. the combination of natural language processing and computer vision techniques are used, an encoder-decoder architecture is employed which aids in leveraging by using a qualified InceptionV3 model to extract image features. the captions which are generated were based on a deep learning model with a Gated Recurrent Unit-based decoder and an attention mechanism, guaranteeing the connection between the generated text to the image content. the research focuses mainly on the dataset which consists of medical images with its associated reports by utilizing data extraction and preprocessing methods to enhance the accuracy and contextual understanding of the generated report. the experiments and results section demonstrate the implementation details and efficacy of the proposed model in generating meaningful report for the medical image, thereby facilitating enhanced interpretation and analysis of medical images. this research contributes to the advancement of image captioning techniques in the medical domain and holds significance for clinical decision support systems and medical image analysis. © 2023 IEEE.

关键词： computer vision Gated Recurrent Unit inception V3 natural language processing

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Community Asset Ontology for Modeling Community Data using information Extraction 6

Community Asset Ontology for Modeling Community Data using I...

引用

6th international conference on Natural language processing and information Retrieval, NLPIR 2022

作者： Chowdhury, Md Towhidul Absar Sharma, Naveen Golisano College of Computing and Information Science Rochester Institute of Technology RochesterNY United States

ISBN: (纸本)9781450397629

In this paper, we analyze some data-related challenges to building resilient and sustainable communities, particularly how to computationally model the social and economical dynamic that exists within a community. To that end, we propose the Community Asset Ontology (CAO) for a knowledge graph that can encapsulate community data as modeled in existing social science literature. We utilize existing information extraction paradigms to map natural language community data to CAO and evaluate the usefulness of such an ontology-based approach compared to a baseline open information extraction approach. © 2022 ACM.

关键词： information retrieval

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A Machine Learning based Facial Expression and Emotion Recognition for Human Computer Interaction through Fuzzy Logic System 6

A Machine Learning based Facial Expression and Emotion Recog...

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6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Vinutha, K. Niranjan, Manoj Kumar Makhijani, Jagdish Natarajan, B. Nirmala, V. Vijaya Lakshmi, T.R. Department of Information Science and Engineering BMS Institute of Technology and Management Karnataka Bengaluru India Department of Computer Applications Rustamji Institute of Technology Madhya Pradesh Gwalior India Department of Computer Science and Engineering Rustamji Institute of Technology Madhya Pradesh Gwalior India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India Department of Science and Humanities Faculty of Engineering Karpagam Academy of Higher Education Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Mahatma Gandhi Institute of Technology Telangana Hyderabad India

ISBN: (纸本)9798350398496

Facial recognition is in use for the past decade there are many applications that needs facial expression to learn the human behaviour and emotions for certain activities. Facial recognition is in a development phase where many service providers use this feature to find the expression of the people on using their BlogSpot or website or reading any news article. this recognition of facial expression is highly possible with the help of machine learning technology. this research study has developed a facial expression recognizing algorithm using Python programming language with the help of Keras software package. this algorithm is purely based on machine learning approach that enables the programmer to process the facial image and convert it into data that is helpful in prediction of facial expression using the fuzzy logic technique. the fuzzy logic technique is a prediction method that helps programmer to predict the intermediate data by providing the initial and ending conditions. For enabling the facial recognition to process any system or a mobile device the algorithm needs permission to access the camera, once the onto the access is permitted the algorithm retrieves the image from the Vision sensor and with the help of image processing technology of the machine learning algorithm the program the program converts the data from the vision sensor into required facial expression and emotional content. © 2023 IEEE.

关键词： Emotion Recognition

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