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Data Processing and pattern recognition for Electronic Nose 3

Data Processing and Pattern Recognition for Electronic Nose

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Raymond, David Chaudhri, Shivnath Shaikh, Kahkasha Datta Meghe Institute of Higher Education and Research Faculty of Enfineering and Technology Department of Computer Science and Medical Engineering Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Enfineering and Technology Depertment of Computer Science and Design Wardha India

ISBN: (纸本)9798331509675

Electronic nose (e-nose) technology has become a powerful tool for identifying and evaluating complex scents in a variety of contexts, such as environmental monitoring, medical diagnostics, and food quality control. This review study looks at how important pattern recognition and data processing are to improving e-nose system performance. This study covered challenges, including data complexity, cross-sensitivity and interference, sensor drift, and a lack of standardization. The article covers several future directions, such as the use of artificial intelligence (AI) and machine learning to advance pattern recognition and predictive analytics, integration with the Internet of Things (IoT) and big data for real-time monitoring, and advancements in sensor technology for improved sensitivity and *** research work is underway towards the development of low power flexible sensors, improved multi sensor fusion Methodologies, smart adaptive algorithms, Application for personalized health monitoring and diagnostics as well to make it green technologies. To move forward with emerging technologies and for e-nose technology to be applicable, it will have to overcome these weaknesses. © 2025 IEEE.

关键词： Electronic nose

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A Method for Vietnamese Sign Language recognition Using a Fusion of RGB and Depth Information Based on an Inflated 3D ConvNet 3rd

A Method for Vietnamese Sign Language Recognition Using a Fu...

引用

3rd international conference on advances in Information and Communication Technology, ICTA 2024

作者： Nguyen, Xuan-Phuoc Nguyen, Thi-Oanh Nguyen, Van-Toi Faculty of Computer Science PHENIKAA Univesity Yen Nghia Ha Dong Hanoi12116 Viet Nam ICT Department FPT University Hanoi Viet Nam Faculty of Electrical and Electronic Engineering PHENIKAA University Yen Nghia Ha Dong Hanoi12116 Viet Nam

ISBN: (纸本)9783031809422

We propose a method for Vietnamese Sign Language (VSL) recognition using a fusion of RGB and Depth information based on the Inflated 3D ConvNet (I3D) architecture. Our approach applies I3D feature extraction independently to RGB and Depth data, concatenates the extracted features, and processes them through the final classification layer. This method leverages the complementary strengths of both data types, enhancing recognition performance. Experimental results show that our method outperforms the original I3D and other fusion strategies, including Early Fusion and Late Fusion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fusion of RGB and Depth Inflated 3DConvNet Sign Language recognition

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Bangla License Plate Detection and recognition Approach Based on Computer Vision for Authentic Vehicle Identification 3rd

Bangla License Plate Detection and Recognition Approach Base...

引用

3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Dhar, Rajib Kumar Khanom, Fahmida Uddin, Khandaker Mohammad Mohi Imam, Md. Hasan Mostafiz, Rafid Institute of Information Technology Noakhali Science and Technology University Noakhali Bangladesh Department of Mathematics American International University—Bangladesh 408/1 Kuratoli Khilkhet Dhaka1229 Bangladesh Department of Computer Science and Engineering Southeast University Dhaka1208 Bangladesh

ISBN: (纸本)9789819739363

Vehicle license plates (LPs) detection and recognition is a fundamental technique in computer vision that plays a crucial role to extract, localize, and authenticate the information of a vehicle. This paper presents an efficient method for Bangla LPs recognition and vehicle authentication using edge analysis and pattern matching algorithm in real-time nature. This method performs four modules as: preprocessing, license plate identification, character recognition, vehicle authentication. A multi-step preprocessing technique has been applied to extract and understand the potential information in case of any uneven images. To identify edge connectivity and uniformity, Canny edge detector provides more promising in contour analysis and character localization. The segmented characters are converted into texts and verified using the pattern matching algorithm by a predefined database. For this research, a database consisting of 3000 automobile license plate photos captured under different climatic circumstances has been compiled. Additionally, we have curated two additional databases consisting of templates for recognition and registered automobiles for the purpose of authentication. The proposed model can achieve accuracy of 96% in LPs detection, 99% in character recognition, and 100% in vehicle authentication by extracted texts from LPs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication

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3rd international conference on Language Processing and Knowledge Management, LPKM 2024

3rd International Conference on Language Processing and Know...

引用

3rd international conference on Language Processing and Knowledge Management, LPKM 2024

ISBN: (纸本)9783031850660

The proceedings contain 29 papers. The special focus in this conference is on Language Processing and Knowledge Management. The topics include: Machine Learning Serving the School Orientation Process;improving Arabic Fake News Detection Across Context-Aware Attention Deep Model Based on Natural Language Processing;towards a Maude-Based Approach for Formal Modeling Deep Neural Networks;Anti-pattern Based IoRT-Aware Business Process Structure Verification Approach;opinion Analysis Based on a Sentiment Lexical Ontology and Deep Learning Models: Tunisian Dialect Case;disfluent-to-Fluent Tunisian Dialect Speech Translation with Fine-Tuning Pre-trained Language Models;BERT-Based Model for Sarcasm Detection in Arabic Texts;typology of Event Data Imperfections;towards Sentiment Analysis for Libyan Dialect;text Categorization Can Enhance Domain-Agnostic Stopword Extraction;normalized Orthography for Tunisian Arabic;deep Learning Approach for Early Prediction of Depression on Social Network;adapting Large Language Models to Biomedical Domain: A Survey of Techniques and Approaches;tunisian Arabic Understanding: Resources Analysis and Evaluation;from Data to Decisions: An Ontology-Driven Method for Opinion Mining;LLMs for Cyberbullying Detection in Political Social Media;Assessing BERT Models for Arabic Named Entity recognition in a Multi-dialectal Context;tunisian Normalized Pronunciation;traffScOnto: Ontology for Traffic Management in the Context of Smart City Domain;SERTUS Dataset Collection from Spontaneous Environments;an Agricultural Sentiment Dataset for Pest Control and Crop Diseases;deep Learning Approach to Identify and Classify Arabic Verbal Multi-word Expressions;a Design pattern-Based Approach for Analyzing MapReduce Applications;analyzing the Impact of Big Data in Mental Health;The Impact of AI on Knowledge Management;a Rule-Based System for Translating Libyan Dialect Dual Forms to Modern Standard Arabic.

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Building an Automatic Attendance System for VNUIS Students Using Convolutional Neural Network 3rd

Building an Automatic Attendance System for VNUIS Students...

引用

3rd international conference on advances in Information and Communication Technology, ICTA 2024

作者： Kim, Thai Dinh Phuong-Thao, D.T. Ha, Manh-Hung Pham, Anh-Phuong Nguyen, Khac-Ton Dao, Ngoc-Nam Nguyen, Khac-Truong Nguyen-Tien, Ha International School Vietnam National University Hanoi100000 Viet Nam Hung Vuong University Phutho Viet Nam

ISBN: (纸本)9783031809422

In traditional classrooms, attendance tracking is often time-consuming and error-prone, relying on manual methods like roll call and sign-in sheets. This paper presents an Automated Attendance System designed specifically for students at Vietnam National University international School (VNU-IS), utilizing face recognition technology to streamline the process. Our system employs Multi-task Cascaded Convolutional Networks (MTCNN) for face detection and alignment and FaceNet for feature extraction and recognition. The recognized faces are classified using Support Vector Machines (SVM), and attendance records are managed with SQLite and Excel for real-time updates. The system was evaluated under various lighting conditions and facial angles, demonstrating high precision and recall, particularly in well-lit environments. This approach enhances the accuracy and efficiency of attendance tracking, reduces manual intervention, and provides valuable insights for educators and administrators. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Students

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A temporal-spatial feature coordination network for change detection of VHR images 3

A temporal-spatial feature coordination network for change d...

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3rd international conference on Geographic Information and Remote Sensing Technology, GIRST 2024

作者： Zeng, Yuxian Zhang, Xinxin College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781510689077

Deep learning techniques have significantly improved the accuracy and efficiency of change detection of very high resolution (VHR) images. However, many current models ignore the inherent heterogeneity of bi-temporal remote sensing images, thus making it difficult to distinguish between target changes and background variations. To address this problem, we propose a deep learning (DL) framework, namely temporal-spatial feature coordination network (TSFCN), to improve the accuracy of detection by enhancing the differentiation of change pixel features and improving the extraction and processing of change information. Further comparison and ablation experiments on the SVCD dataset show that the proposed model, compared with other models, improves the F1 scores and IoU by 2.09% and 3.81%, respectively. The results demonstrate that our model can achieve better accuracy and performance improvement. © 2025 SPIE.

关键词： Change detection

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3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

3rd International Conference on Computational Electronics fo...

引用

3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

ISBN: (纸本)9789819719457

The proceedings contain 35 papers. The special focus in this conference is on Computational Electronics for Wireless Communications. The topics include: Design of a Four-Port MIMO Antenna for C-, X-, and Ku-Band Applications;Exploration of Diverse Techniques for Design and Optimization of QCA-Based Multiplexer Circuits;melanoma Detection Via Deep Convolutional Neural Network;pattern Diversity mm-Wave Rectangular Ring Shaped MIMO Antenna for 5G Communication and Internet of Things Applications;Flexible Two/Eight-Port MIMO Antenna Configuration for LTE B41/WLAN/Wi-Fi 6E and C-Band Applications;Improvement in Machining Ability of Tungsten Carbide Tool Insert Through Microwave Hybrid Heating During Turning of EN 24 Steel;optimizing Airfare Pricing: A Data-Driven Approach for Affordable Travel Planning;advancements in Emotion recognition: Systematic Review and Research Roadmap;epoc-Based Electroencephalography Signals Analysis of Different Stress Levels;Two-Element Tilted Rectangular MIMO UWB Antenna for Underwater Communications;deep Learning-Based Maize Crop Disease Detection and Remedial Recommendation System;design of Splash Plate Dielectric Hat Feed for Ka-Band Tracking Radar Applications;soft Computing Paradigms for Load Balancing in Cloud Computing;strategies for Effective Network Congestion Control: Insights from Parameter-Based Analysis;BICC: Optimizing Sensor Network Performance Via an Efficient Bioinspired Iterative Approach with Congestion Control;Leakage Power Reduction and Stability Analysis of 5 nm Node GAA CNTFET SRAMs;bandwidth Enhancement and Improvement of Directivity of a Composite Conical Structure in the Presence of a Circular Loop Antenna;development of Compact Dual Polarized Corrugated Feed Horn Antenna with Low Cross-Polarization for Doppler Weather Radar Applications in C-Band;A Review on Recent Breakthroughs and Accomplishments in the Development of FeFET.

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3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

3rd International Conference on Computational Electronics fo...

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3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

ISBN: (纸本)9789819719426

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international JOINT conference ON pattern recognition, 3rd, PROCEEDINGS, 1976.

INTERNATIONAL JOINT CONFERENCE ON PATTERN RECOGNITION, 3RD, ...

引用

Int Jt Conf on pattern recognition, 3rd, Proc

作者： Anon

One hundred and fifty-six papers were presented at the Third international Joint conference on pattern recognition. The individual sessions covered the following topics: Industrial Applications;Feature Extraction and Primitive Selection;Syntactic Methods in pattern Analysis;Optical Character recognition;Learning Algorithms and Sample Size;Line Drawing and Waveform Processing;Interactive pattern Analysis;Statistical pattern recognition Theory;Perceptual Modeling;pattern recognition Competition;General Applications;Clustering;Linguistic Applications and Natural Language Processing;Theoretical Problems;Segmentation and Shape Encoding;Medical Image Processing and pattern Analysis;Picture Description and Scene Analysis;Speech recognition and Data Compression;Remote Sensing;Parallel Processing and Two-Dimensional Digital Filtering;Edge, Line and Object recognition;Applications of pattern recognition Technique;Image Analysis and Texture;Data Base Computer Systems.

关键词： pattern recognition systems

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Electrical Power Enterprise Training System Based on Interactive 3D Virtual Reality

Electrical Power Enterprise Training System Based on Interac...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE international conference on

作者： Qin Li Electric Power of Henan Zhengzhou China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

In recent years, the electrical power enterprises require skilled personnel to operate and maintain the complex systems. The trainees need effective training for the systems to ensure safety, efficiency and reliability. The existing electrical power system faced several challenges due to complex systems and high voltage risks with limited hands-on experience. To overcome these issues, interactive 3D Virtual Reality (3D-VR) is proposed for maintaining realistic experience for the trainees. Initially, the Building Information Modelling (BIM) is utilized to generate 115 kV substation data for an accurate 3D model of electric power training system. Further, the BIM model is integrated with VR simulator, where it enables immerse experience for trainees in the substation environment. Then, the interactive 3D simulator is employed to create a realistic environment for enterprise training system to the trainers. Finally, Convolutional Neural Network (CNN) model is incorporated to evaluate the performance with complex pattern recognition. At last, the CNN model detects the unusual behaviors of trainees based on probability threshold and provides personalized feedback. From the results, the proposed interactive 3D-VR attained better results in terms usability (68.23 % ) and Learnability (45.32 % ) of when compared to existing VR.

关键词： Training Solid modeling Adaptation models Three-dimensional displays Substations Virtual reality pattern recognition Convolutional neural networks Integrated circuit modeling Usability

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