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检索条件"任意字段=4th IASTED International Conference on Signal Processing, Pattern Recognition and Applications"

共 162 条记录，以下是11-20 订阅

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4th Annual international conference on Data Science, Machine Learning and Blockchain Technology, AICDMB 2023

4th Annual International Conference on Data Science, Machine...

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4th Annual international conference on Data Science, Machine Learning and Blockchain Technology, AICDMB 2023

ISBN: (纸本)9781032426853

the proceedings contain 50 papers. the special focus in this conference is on Data Science, Machine Learning and Blockchain Technology. the topics include: An unsupervised approach to creating a restaurant recommendation system;Classification of alzheimer’s disease using D-DEMNET framework;comparison of machine learning and deep learning methods for detection of liver abnormality;soil micronutrient detection using machine learning;a review of tracking concept drift detection in machine learning;wearable electrogastrogram perspective for healthcare applications;computer vision based home automation;Early autism detection using ML on behavioural pattern;implementation of application prototypes for human-to-computer interactions;recommendation system for anime using machine learning algorithms;predicting bitcoin price fluctuation by Twitter sentiment analysis;microarchitecture design and verification of co-processor for floating point operation;blockchain based higher education ecosystem;document verification using blockchain;blockchain-based traceability system for readymade food products;a cloud based interactive framework for emergency medical data sharing;the analysis and interpretation of higher education teachers based on student and teachers feedback;Implementing AI on microcontrollers in fog and edge architectures;abnormality detection in chest radiograph using deep learning models;a comprehensive review on hate speech recognition utilizing natural language processing and machine learning;prevalence of migraine among collegiate students in greater Noida;Indoor navigation using BLE beacons;strategic health planner and exercise suggester;perspective of deep learning strategies for analysis of 1D biomedical signals;revolution in agriculture sector using blockchain technology;customer churn prediction using ensemble learning with neural networks;Securing crime case summary and E-FIR using blockchain concept.

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4th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023

4th EAI International Conference on Cognitive Computing and ...

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4th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023

ISBN: (纸本)9783031488900

the proceedings contain 39 papers. the special focus in this conference is on Cognitive Computing and Cyber Physical Systems. the topics include: Drug Recommendations Using a Reviews and Sentiment Analysis by RNN;optimizing Real Estate Prediction - A Comparative Analysis of Ensemble and Regression Models;estimation of Power Consumption Prediction of Electricity Using Machine Learning;medical Plants Identification Using Leaves Based on Convolutional Neural Networks;An Efficient Real-Time NIDS Using Machine Learning Methods;Maixdock Based Driver Drowsiness Detection System Using CNN;A Novel Approach to Visualize Arrhythmia Classification Using 1D CNN;exploring Machine Learning Models for Solar Energy Output Forecasting;the Survival Analysis of Mental Fatigue Utilizing the Estimator of Kaplan-Meier and Nelson-Aalen;an Optimized Ensemble Machine Learning Framework for Multi-class Classification of Date Fruits by Integrating Feature Selection Techniques;EEMS - Examining the Environment of the Job Metaverse Scheduling for Data Security;text Analysis Based Human Resource Productivity Profiling;a Novel Technique for Analyzing the Sentiment of Social Media Posts Using Deep Learning Techniques;comparative Analysis of Pretrained Models for Speech Enhancement in Noisy Environments;Use of Improved Generative Adversarial Network (GAN) Under Insufficient Data;unraveling the Techniques for Speaker Diarization;LUT-Based Area-Optimized Accurate Multiplier Design for signal processing applications;speaker recognition Using Convolutional Autoencoder in Mismatch Condition with Small Dataset in Noisy Background;face Emotion recognition Based on Images Using the Haar-Cascade Front End Approach;textRank – Based Keyword Extraction for Constructing a Domain-Specific Dictionary;harmonizing Insights: Python-Based Data Analysis of Spotify's Musical Tapestry;Enlighten GAN for Super-Resolution Images from Surveillance Car.

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4th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023

4th EAI International Conference on Cognitive Computing and ...

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4th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023

ISBN: (纸本)9783031488870

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Analysis of Bangla Transformation of Sentences Using Machine Learning 1

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4th international conference on Deep Learning, Artificial Intelligence and Robotics, ICDLAIR 2022

作者： Das, Rajesh Kumar Sammi, Samrina Sarkar Kobra, Khadijatul Ajmain, Moshfiqur Rahman khushbu, Sharun Akter Noori, Sheak Rashed Haider Daffodil International University Dhaka1341 Bangladesh

ISBN: (数字)9783031303968

ISBN: (纸本)9783031303951

In many languages, various language processing tools have been developed. the work of the Bengali NLP is getting richer day by day. Sentence pattern recognition in Bangla is a subject of attention. Additionally, our motivation was to work on implementing this pattern recognition concept into user-friendly applications. So, we generated an approach where a sentence (sorol, jotil and jougik) can be correctly identified. Our model accepts a Bangla sentence as input, determines the sentence construction type, and outputs the sentence type. the most popular and well-known six supervised machine learning algorithms were used to classify three types of sentence formation: Sorol Bakko (simple sentence), Jotil Bakko (complex sentence) and Jougik Bakko(compound sentence). We trained and tested our dataset, which contains 2727 numbers of data from various sources. We analyzed our dataset and got accuracy, precision, recall, f1-score and confusion matrix. We get the highest accuracy with the decision tree classifier, which is 93.72%. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Empirical Analysis of Hybrid Classical Variational Quantum Neural Networks for Target Classification from SAR Data 4th

Empirical Analysis of Hybrid Classical Variational Quantum ...

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4th international conference on Machine Intelligence and signal processing, MISP 2022

作者： Gajjar, Pranshav Saxena, Aayush Ranpariya, Divyesh Shah, Pooja Das, Anup Institute of Technology Nirma University Ahmedabad India SRM Institute Of Science and Technology Chennai India Space Applications Centre ISRO Ahmedabad India

ISBN: (纸本)9789819900848

the advancements in the field of quantum machine learning and the ability of quantum-enhanced networks to acquire a higher effective dimension are promising for remote sensing applications and synthetic aperture radar (SAR) data. this paper aims to incorporate variational quantum circuits with existing classification-based deep learning state-of-the-art architectures. Tests are proposed by using ResNets, DenseNets, and a SqueezeNet-based convolutional neural network. Various dressed quantum circuits associated with these encoders are created and tested for novel applicability analysis. A famous publicly available X-Band SAR image-based dataset called moving and stationary target acquisition and recognition (MSTAR) is utilized to demonstrate image-centric target classification. the utility of quantum-enhanced and hybrid classical-quantum transfer learning models is provided. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Synthetic aperture radar

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4th international conference on Recent Trends in Image processing and pattern recognition, RTIP2R 2021

4th International Conference on Recent Trends in Image Proce...

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4th international conference on Recent Trends in Image processing and pattern recognition, RTIP2R 2021

ISBN: (纸本)9783031070044

the proceedings contain 33 papers presendted at a virtual meeting. the special focus in this conference is on Recent Trends in Image processing and pattern recognition. the topics include: Real-Time Face recognition for Organisational Attendance Systems;Harnessing Sustainable Development in Image recognition through No-Code AI applications: A Comparative Analysis;evaluating Performance of Adam Optimization by Proposing Energy Index;an Alignment-Free Fingerprint Template Protection Technique Based on Minutiae Triplets;early Prediction of Complex Business Processes Using Association Rule Based Mining;A Framework for Masked-Image recognition System in COVID-19 Era;A Deep-Learning Based Automated COVID-19 Physical Distance Measurement System Using Surveillance Video;Detection of Male Fertility Using AI-Driven Tools;face Mask Detection Using Deep Hybrid Network Architectures;a Super Feature Transform for Small-Size Image Forgery Detection;UHTelHwCC: A Dataset for Telugu Off-line Handwritten Character recognition;inflectional and Derivational Hybrid Stemmer for Sentiment Analysis: A Case Study with Marathi Tweets;adaptive threshold-Based Database Preparation Method for Handwritten Image Classification;a Graph-Based Holistic recognition of Handwritten Devanagari Words: An Approach Based on Spectral Graph Embedding;Imagined Object recognition Using EEG-Based Neurological Brain signals;a Fast and Efficient K-Nearest Neighbor Classifier Using a Convex Envelope;single Channel Speech Enhancement Using Masking Based on Sinusoidal Modeling;extraction of Temporal Features on Fibonacci Space for Audio Based Vehicle Classification;an Empirical Study of Vision Transformers for Cervical Precancer Detection;An Improved Technique for Preliminary Diagnosis of COVID-19 via Cough Audio Analysis;agricultural Field Analysis Using Satellite Hyperspectral Data and Autoencoder;Development of NDVI Prediction Model Using Artificial Neural Networks;time Series Forecasting of Soil Moisture Using Sa

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Towards Adversarial Robustness and Reducing Uncertainty Bias through Expert Regularized Pseudo-Bidirectional Alignment in Transductive Zero Shot Learning 27th

Towards Adversarial Robustness and Reducing Uncertainty Bias...

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27th international conference on pattern recognition, ICPR 2024

作者： Kumar Sinha, Abhishek Mishra, Deepak Moorthi, S. Manthira Signal and Image Processing Area Space Applications Center Ahmedabad India Indian Institute of Space Science and Technology Thiruvananthapuram India

ISBN: (纸本)9783031781827

Transductive zero-shot learning (TZSL) aims to minimize the domain shift between the learned and true distribution of the unseen classes by allowing access to the unpaired samples from unseen classes. While many distribution alignment based methods attempt to align both visual and semantic spaces to train the classifier, their performance is still limited by confirmation bias. Additionally, bidirectional alignment approaches are based on the strong assumption that the intrinsic dimensions of visual and semantic spaces are the same, which is rarely true. In this work, we first highlight the limitations of bidirectional alignment in terms of intrinsic dimensionality. We then present a pseudo-bidirectional approach that, without any underlying assumptions on these spaces, utilizes the learned visual-to-attribute mapping to minimize the distribution shift between learned and true unseen visual feature distributions. We further utilize an entangled loss between semantic and visual space to minimize the confirmation or uncertainty bias and improve the adversarial robustness. We, theoretically and empirically, show the performance gain in addition to the adversarial robustness under the proposed setting. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Slotted Hexagonal Ultrawideband Microstrip Antenna (SHUMA) for Telemetry applications

Slotted Hexagonal Ultrawideband Microstrip Antenna (SHUMA) f...

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international conference on signal processing and Communication (ICSPC)

作者： Melbin Elsa Cheriyan Rahul Krishnan Ramu R Glintu Joy Abina Ann Mathew Shefin Shaji Electronics and Communication Engineering Mar Baselios Christian College of Engineering & Technology Idukki India

the fields of biomedicine and healthcare have recently shown a great deal of interest in the investigation of flexible wireless devices. Human bodies produce a tremendous amount of information. therefore, we present a small, slotted hexagonal patch antenna for use in biomedical applications. Lightweight and semi-flexible Rogers RT duroid 5880 material is used in the antenna’s construction. the incorporation of slots and partial ground structure aided in boosting the operating performance of the antenna. Using Computer Simulation Technology (CST) software, the proposed antenna’s performance is evaluated in terms of bandwidth, return loss, gain, radiation pattern, directivity, total efficiency, and power.

关键词： Wireless communication Slot antennas Microstrip antennas Bandwidth signal processing Ultra wideband antennas Software

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Efficient Neural Network Design for Radar signal recognition

Efficient Neural Network Design for Radar Signal Recognition

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Data Science and Computer Application (ICDSCA), IEEE international conference on

作者： Haicheng Li Chao Li The 20th Research Institute of China Electronics Technology Group Corporation Xi'an China

ISBN: (数字)9798350368239

ISBN: (纸本)9798350368246

In this paper, we propose an innovative approach to the problem of radar signal recognition, which is based on Neural Architecture Search (NAS). With the development of radar technology, radar signals become more and more diverse and complex, which brings great challenges to the traditional signal processing methods. therefore, this paper aims to explore a more efficient and intelligent radar signal recognition scheme. the core contribution of this paper is the introduction of NAS technology to radar signal recognition. Unlike traditional deep learning-based methods that require manual design of the network structure, our approach automatically finds the optimal neural network structure through a pre-defined search space and search strategy. this method not only greatly reduces the time and effort required by the researchers to design the network structure, but also guarantees the performance superiority of the network model. Specifically, by automating the search process, we can find network architectures that are better suited to handling specific types of radar signals, thus improving the accuracy and efficiency of identification. To assess the validity of our proposed method, we undertook extensive experimentation across various standard datasets. the results of these experiments indicate that, in comparison to several existing sophisticated methods, our method has enhanced recognition accuracy, particularly in the handling of intricate and variable radar signals.

关键词： Accuracy Spaceborne radar Neural networks Radar Network architecture Search problems Radar signal processing Radar applications Neural architecture search Standards

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A Microstrip Patch Antenna with High Gain for WiMAX and X-Band applications

A Microstrip Patch Antenna with High Gain for WiMAX and X-Ba...

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international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Maria Sultana Tofavel Karim Mohammad Abdul Alim Electrical and Electronic Engineering University of Chittagong Chattogram Bangladesh

ISBN: (数字)9798331530952

ISBN: (纸本)9798331530969

the microstrip patch antenna was specifically designed to be operational at a frequency of 7.8 GHz for applications in WiMAX and X-band satellite communication. the proposed design utilized a patch with optimized dimensions on Rogers RT/duroid substrate with a permittivity of 2.2 and a thickness of 1.5 mm. the patch of the antenna comprised two patch elements that were connected to each other. Adding the second patch enhanced the antenna's performance by improving its return loss to -49.92 dB and VSWR to 1.006 along with achieving an optimal gain of 8.5 dB. the antenna demonstrated a resonant frequency of 7.8 GHz with a stable radiation pattern, low return loss (-49.92 dB), low VSWR, and high gain of about 8.5 dB.

关键词： Patch antennas Impedance matching Microstrip antennas WiMAX Directive antennas Reflector antennas Microstrip Gain Substrates Antenna radiation patterns

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