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检索条件"任意字段=8th IFIP International Conference on Engineering for Human-Computer Interaction"

共 2025 条记录，以下是71-80 订阅

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Enhancing Image Captioning through the Integration of Image Processing and NLP 8

Enhancing Image Captioning through the Integration of Image ...

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8th IEEE international conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Ugale, Sakshi Jain, Druwil Chikmurge, Diptee Barve, Sunita S. Mit Academy of Engineering School of Computer Engineering Alandi Dist. Pune India

ISBN: (纸本)9798350391770

the study offers a novel method for captioning images by combining Gated Recurrent Units (GRU) and Convolutional Neural Networks (CNN). A feature extractor called VGG19 can be used to take complex photos and extract high-level visual representations from them. the aforementioned visual inputs are subsequently fed into a language model that employs a GRU and Bi-directional LSTM, two widely recognised models for handling sequential dependencies, to produce captions that make sense and are contextually relevant. Selective information update is made possible by the GRU's gating mechanism, making it simpler to capture long-range dependencies in the output captions. the combination of VGG19, GRU, and Bi-directional LSTM provides a comprehensive and hierarchical method for photo captioning that extracts rich visual information required for comprehending complex picture content. GRU's gating technique makes it easier to analyse specific information, which improves the model's comprehension of complex relationships found in output captions. In order to provide more accurate image descriptions, the suggested methodology seeks to improve the synergy between visual and verbal knowledge. Comparing experimental assessments against modern technique approaches on benchmark datasets with metrics like BiLingual Evaluation Understudy (BLEU), METEOR, and CIDEr shows encouraging results. In addition to its potential uses in computer vision(CV), accessibility, and human-computer interaction, this work advances the field of image caption development. © 2024 IEEE.

关键词： Convolutional neural networks

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Considering Modelling Techniques in HCI engineering Education 19th

Considering Modelling Techniques in HCI Engineering Educatio...

引用

19th international-Federation-for-Information-Processing-Technical-Committee-13 (ifip TC13) international conference on human-computer interaction (INTERACT)

作者： Martinie, Celia Univ Toulouse III Paul Sabatier ICS IRIT Toulouse France

ISBN: (纸本)9783031616877;9783031616884

Teaching HCI engineering focuses on preparing students for the design, development, and implementation of usable and effective interactive computing systems. Amongst the engineering approaches that can be taught for that purpose, model-based techniques are interesting because they match the industry's needs for techniques to develop usable and reliable interactive computing systems. Beyond this concrete motivation for teaching students how to build and use models, models are also interesting because they help students to reason and understand problems, and can even make them better at identifying and solving problems. However, students do not always understand the benefits of using modelling techniques. they may find them abstract, cumbersome, and worthless. the purpose of this paper is to discuss the importance of teaching modelling for HCI engineering, especially in a context where new technologies and new methodology trends are continuously emerging. this paper proposes several strategies to increase the involvement of students with modelling techniques.

关键词： HCI education engineering Interactive Computing Systems Modelling techniques

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A Smart Interactive Behavioral Chatbot: A theoretical Prototype 8

A Smart Interactive Behavioral Chatbot: A Theoretical Protot...

引用

8th international engineering conference on Renewable Energy and Sustainability, ieCRES 2023

作者： Alwahaishi, Saleh King Fahd University of Petroleum & Minerals Department of Information Systems and Opeations Management Saudi Arabia King Fahd University of Petroleum & Minerals Dhahran Interdisciplinary Research Center for Finance & Digital Economy Saudi Arabia

ISBN: (纸本)9798350300758

In recent years, significant advancements have been made in speech and language understanding research, with a particular focus on the development of conversational dialog systems between humans and machines. these systems, also recognized as chatbots, interactive conversational agents, or dialog systems, have broad applications, including technical support services, language entertainment, and learning. the emergence of deep neural networks has surged research efforts aimed at building data-driven dialog models. In this study, a novel approach is introduced that incorporates emotions extracted from various sources to design a smart and interactive chatbot. © 2023 IEEE.

关键词： human computer interaction

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An NLP Based Approach to Automate and Enhance the Systematic Review Within PRISMA Format 8th

An NLP Based Approach to Automate and Enhance the Systematic...

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8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： thankachan, Jeena A. Srinivasan, Bama Department of Information Science and Technology College of Engineering Anna University Tamilnadu Guindy Chennai600025 India

ISBN: (纸本)9783031736162

Systematic Literature Review (SLR) is an integral part of research;however, to conduct an SLR, the manual review process would be time-consuming due to the high volume of literature involved. this paper presents a method that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to automate the systematic review process at two key stages: screening and eligibility assessment. the approach utilizes BERT (Bidirectional Encoder Representations from Transformers) embeddings and cosine similarity for automated label assignment and categorization of research articles. the proposed approach aligns to the principles of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) in the automation of the domain based categorization of articles, and resolves the challenges posed by the state of art techniques. the proposed work considers three datasets with total 2164 records, collected based on identification criteria of PRISMA, to be classified into three categories. the proposed method based on BERT gives good results on categorization of article with an accuracy of 99% , 98% and 96% for each dataset. © ifip international Federation for Information Processing 2025.

关键词： Embeddings

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Perl eBook: Unleashing Machine Learning with *** in a *** and SQL Environment 8th

Perl eBook: Unleashing Machine Learning with *** in a *** an...

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8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Nivethitha Devi, M. Jeyaprakash, N. Sanjay, R. Shashwat, B.R. St. Joseph’s College of Engineering Chennai600119 India

ISBN: (纸本)9783031736162

the Perl eBook platform revolutionizes the digital reading experience by seamlessly merging traditional thematic values encapsulated in the Perl acronym (Publish, Enlighten, Read, and Listen) with cutting-edge technologies. this dynamic platform not only provides free access to a diverse collection of books, encouraging the exploration of various genres, but also introduces an innovative shopping feature for users to purchase books. In addition to freely reading ebooks, users can actively contribute to the platform by publishing their own works, subject to evaluation, thereby fostering a collaborative and enriching literary community. To ensure inclusivity and promote quality education, the platform offers audio books for the visually impaired, further expanding its accessibility. the integration of ***, SQL, and *** enhances the user experience, providing personalized content recommendations. A central aspect is the inclusion of a chatbot for real-time assistance, contributing to a user-friendly environment. © ifip international Federation for Information Processing 2025.

关键词： Adversarial machine learning

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Implementing a NFT Based Album Purchasing Web Application Using ReactJs by Integrating with Ethereum Blockchain 8th

Implementing a NFT Based Album Purchasing Web Application Us...

引用

8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： thamizhselvi, D. Shabika Fathima, M. Dhivya, M. Srinidhi, M. Sri Sairam Engineering College Sai Leo Nagar Poonthandalam Village West Tambaram Chennai600044 India

ISBN: (纸本)9783031736162

Blockchain is one of the emerging technologies, which is trustless, decentralized and secure. In today’s world blockchain can be almost applicable anywhere. Using blockchain technology in the music industry, where many artists lose their music ownership and revenue to streaming platforms and production houses. Blockchain can be utilized to overcome this problem faced by artists, by using the concept of Non Fungible Token (NFTs). A dynamic web application built using ReactJs for the artist to mint their NFTs and store the metadata in off-chain using IPFS protocol and an ERC721 smart contract built using Solidity is deployed to Ethereum Blockchain and the IPFS CID along with the contract address is stored in MySql database using SpringBoot data Jpa and RESTful API for rendering data in webpage. Graph protocol is used for indexing and querying smart contract transactions and it is visualized using ChartJs. © ifip international Federation for Information Processing 2025.

关键词： Ethereum

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Automated Depression Detection Using CNN and Transformer-Based Pre-trained Language Models 8th

Automated Depression Detection Using CNN and Transformer-Bas...

引用

8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Ramalakshmi, N.R. Kumar, Meghna Ganesh Raghavi, S. St. Joseph’s College of Engineering OMR Tamil Nadu Chennai India

ISBN: (纸本)9783031736162

the research focuses on the automation of depression detection through the integration of Convolutional Neural Networks (CNNs) and Transformer-based Pre-Trained Language models. Traditionally, depression assessment relied on comprehensive clinical interviews where psychologists analyzed responses to assess an individual’s mental state. In this model, the replication of this process incorporates three modalities: word context, audio, and video. through the fusion of these modalities, the prediction of an individual’s mental health status is achieved. the deep learning model encompasses three distinct data modalities, each representing different degrees of depression experienced by the subject. the model assigns appropriate weights to each modality, generating output based on their collective influence. this research contributes to advancing depression monitoring by employing cutting-edge deep learning techniques to analyze multi-modal data, leveraging independent learning synergies for enhanced accuracy. © ifip international Federation for Information Processing 2025.

关键词： Convolutional neural networks

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DestiNexus: Probabilistic Framework for Weather- Informed Travel Itinerary Optimization 8th

DestiNexus: Probabilistic Framework for Weather- Informed Tr...

引用

8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Ranjeeth Kumar, R. Naina, S. S. M. Mahudoom Muthulakshmi, V. Department of Information Technology St. Joseph’s College of Engineering TamilNadu Chennai India

ISBN: (纸本)9783031736162

DestiNexus is revolutionizing travel planning by utilizing a combination of advanced models to provide comprehensive and accurate recommendations. these include the cutting-edge RandomForestRegressor model for precise weather predictions, a RandomForestClassifier for accurate binary rain prediction, and an ARIMA model for effective time-series forecasting. the integration of ReactJS Front End and Backend Server allows for seamless collaboration and personalized suggestions based on factors such as location, date, and time. With a multi-model approach, DestiNexus not only offers specific predictions but also utilizes probabilistic modeling to provide users with valuable prediction intervals. Combining the power of machine learning, probabilistic techniques, and user-friendly design, DestiNexus offers a dynamic and immersive travel planning experience. Rigorous evaluation metrics, including Mean Squared Error and classification accuracy, underscore the reliability of its predictions. In essence, DestiNexus sets a new paradigm in travel planning, catering to a more nuanced and informed exploration of the world. © ifip international Federation for Information Processing 2025.

关键词： Weather forecasting

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Integrating Deep Learning Frameworks for Automated Medical Image Diagnosis 8th

Integrating Deep Learning Frameworks for Automated Medical I...

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8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Gayatri, K. Kumar, K. M. Anand Padmavathi, B. Shankar Department of Computer Science and Engineering Easwari Engineering College Ramapuram Chennai600089 India

ISBN: (纸本)9783031736162

In today’s healthcare system, medical image analysis is essential for diagnosis, treatment planning, and condition monitoring. In this study, the four well-known tools in the field are 3D Slicer, MONAI, SAMM, and YOLOv8 are examined and contrasted. the study’s scope includes its ability to process a variety of 2D and 4D medical imaging datasets, which contain images, segmentation, annotations, and transformations. the process entails a comprehensive prehensive examination of every tool’s feature, with particular emphasis on their capacity to read and write DICOM images, accommodate multiple file formats, offer interactive 3D Slicer. Key findings show that 3D Slicer performs exceptionally well when using deep learning techniques for segmentation and interactive visualization. While SAM Model exhibits adaptability in managing diverse segmentation prompts, MONAI provides a comprehensive end-to-end medical data processing solution. YOLOv8 shows potential for effective object detection. the study’s implications include the possibility of using these instruments in clinical practices and medical research contexts. the research results provide insight into the current discussion about how to strategically integrate state-of-the-art methods to improve overall healthcare outcomes, diagnostic accuracy, and treatment planning efficiency as medical image analysis continues to advance. © ifip international Federation for Information Processing 2025.

关键词： Clinical research

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Dynamic Gesture Recognition Method Based on Self-Learning Sparse Representation 8

Dynamic Gesture Recognition Method Based on Self-Learning Sp...

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8th international conference on Information Systems engineering, ICISE 2023

作者： Kong, Dehua Zhang, Bo Lu, Lin Wuhan Donghu University School of Computer Science Wuhan China The China CITIC Mobile Communication Technology Co. Procurement Center Wuhan China

ISBN: (纸本)9798350307009

Using wireless body area networks to monitor and recognize human motion is one of the research hotspots in wireless body area networks, and gesture is an important component of human motion. Gesture, as a natural, intuitive, and easy to learn human-computer interaction method, can provide operational convenience for health monitoring in wireless body area networks. Gestures are divided into static and dynamic gestures. Static gestures rely solely on the external shape and contour information of the hand to convey information. Dynamic gestures also include gesture timing information for gesture movements, which can express richer and more accurate information. Data acquisition methods for gesture movements include data glove based, vision based, EMG based, and inertial sensor based methods. this paper studies a dynamic gesture recognition method based on acceleration sensors. © 2023 IEEE.

关键词： Gesture recognition

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