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检索条件"任意字段=Conference on Visual Communications and Image Processing 94"

共 3973 条记录，以下是21-30 订阅

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Using Convolutional Neural Networks for image Recognition in IoT Applications

Using Convolutional Neural Networks for Image Recognition in...

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2025 International conference on Pervasive Computational Technologies, ICPCT 2025

作者： Rajababu, Durgam Veerraju, Sampenga Kumar, K. Suresh Gupta, Sonali Thurai Raaj, V.B. Joshi, Rahul Sr University School of Engineering Department of Eee Telangana Warangal India Dadi Institute of Engineering and Technology Department of Electronics and Communications Engineering Andhra Pradesh Anakapalli Visakhapatnam531002 India Panimalar Engineering College Mba Department Varadarajapuram Poonamallee Chennai600123 India J C Bose University of Science and Technology Ymca Faridabad India Madanapalle Institute of Technology & Science Electrical and Electronics Engineering Andhra Pradesh Madanapalle India Manav Rachna International Institute of Research and Studies Department of Journalism & Mass Communication SMeH Haryana India

ISBN: (纸本)9798331508685

Convolutional Neural Networks (CNNs) have grown into a powerful picture identification tool. They are an important part of making Internet of Things (IoT) apps. In this regard, CNNs make it possible to analyse visual data gathered from networked devices, like cameras and sensors, effectively and accurately. With an emphasis on its potential for real-time applications for example smart surveillance, healthcare monitoring, autonomous cars, and industrial automation, this study investigates the incorporation of CNN-based image identification into IoT contexts. We tackle important issues such as the requirement for low-latency processing, energy economy, and computing limitations on edge devices. In order to maximise CNN performance in the resource-constrained IoT ecosystem, strategies like model compression, edge computing, and distributed architectures are covered. The ability to interpret large volumes of visual data is improved by the integration of CNNs with IoT, providing creative solutions for automation and intelligent decision-making across numerous industries. © 2025 IEEE.

关键词： Convolution

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9th International conference on image processing and communications, IP and C 2017

9th International Conference on Image Processing and Communi...

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9th International conference on image processing and communications, IP and C 2017

ISBN: (纸本)9783319687193

The proceedings contain 22 papers. The special focus in this conference is on image processing and communications. The topics include: Binary line oriented histogram;image search enhanced by using external data sources and reasoning;linguistic description of images based on fuzzy histograms;using toboggan segmentation in detection of centers and radius of cell nuclei;evaluation of the pre-processing methods in image-based palmprint biometrics;on the way to perfect steganography;PET waste classification method and plastic waste database – wadaba;estimation of geometrical deformations of 3D prints using local cross-correlation and monte carlo sampling;quality assessment of 3D printed surfaces in fourier domain;the adaboost algorithm with linear modification of the weights;evaluation of hashing methods performance on binary feature descriptors;efficient parallelization methods of labeling algorithm;modeling telecommunication networks with the use of reference graphs;QoS concept for protecting network resources - a case study;acceleration of genome sequencing with intelligent cloud brokers;learning management systems on blended learning courses;technology and software for calculating correct normalization of correlation functions;running sports decision aid tool based on reinforcement learning approach;framework for evaluating QoE for remote control of autonomous cars in mobile wireless networks;practical advices for university teachers and comparison of visual descriptors for 3D reconstruction of non-rigid planar surfaces.

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5th International conference in image processing and communications, IP&C 2013

5th International Conference in Image Processing and Communi...

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5th International conference in image processing and communications, IP&C 2013

ISBN: (纸本)9783319016214

The proceedings contain 52 papers. The special focus in this conference is on image processing and communications. The topics include: Adaptive windowed threshold for box counting algorithm in cytoscreening applications;corneal endothelial grid structure factor based on coefficient of variation of the cell sides lengths;a distributed approach for development of deformable model-based segmentation methods;enhancement of low-dose CT brain scans using graph-based anisotropic interpolation;using of EM algorithm to image reconstruction problem with tomography noises;the perception of humanoid robot by human;a fast histogram estimation based on the Monte Carlo method for image binarization;adaptation of the combined image similarity index for video sequences;time-frequency analysis of image based on stockwell transform;2DKLT-based color image watermarking;knowledge transformations applied in image classification task;problems of infrared and visible-light images automatic registration;semantics driven table understanding in born-digital documents;contextual possibilistic knowledge diffusion for images classification;image feature extraction using compressive sensing;a modification of the parallel spline interpolation algorithms;local Eigen background substraction;polarization imaging in 3D shape reconstrucion;layer image components geometry optimization;extraction of data from limnigraf chart images;a simplified visual cortex model for efficient image codding and object recognition;fuzzy rule-based systems for optimizing power consumption in data centers;an algorithm for finding shortest path tree using ant colony optimization metaheuristic and a sensor network gateway for IP network and SQL database.

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image Captioning Using Scene Graph Generation

Image Captioning Using Scene Graph Generation

引用

International conference on Wireless communications, Signal processing and Networking (WiSPNET)

作者： Shiny S Abisheak A Balaji P Rohit K Department of Artificial Intelligence Mepco Schlenk Engineering College Sivakasi India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

Understanding and generating natural language descriptions from images is a fundamental challenge in vision-language tasks within artificial intelligence. This paper introduces a novel image captioning framework that integrates scene graph generation to improve the semantic richness of generated captions. The proposed method employs the Relation Transformer (RelTR) model to extract structural representations from visual scenes in the form of subject-predicate-object triplets. A transformer-based captioning model then utilizes these structured scene graphs to produce fluent and contextually accurate captions. Experimental evaluations on the visual Genome dataset demonstrate that our approach yields superior semantic coherence and captioning accuracy compared to traditional image-to-text models. The incorporation of relational scene understanding results in captions that are more contextually informed and descriptive.

关键词： Wireless communication visualization Accuracy Semantics Genomics Signal processing Transformers SPICE Bioinformatics Context modeling

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International conference on image processing and communications, IP and C 2015

引用

International conference on image processing and communications, IPandC 2015

ISBN: (纸本)9783319238135

The proceedings contain 34 papers. The special focus in this conference is on image processing and communications. The topics include: Classifier selection uses decision profiles in binary classification task;2DHMM-based face recognition method;corner detection based on directional gradients;sensor fusion enhancement for mobile positioning systems;thermal face recognition;feature reduction using similarity measure in object detector learning with haar-like features;assessment of the brain coverage ratio in the postoperative craniosynostosis based on 3D CT scans;combined imaging system for taking facial portraits in visible and thermal spectra;the PUT surveillance database;automatic analysis of vehicle trajectory applied to visual surveillance;algorithmically optimized AVC video encoder with parallel processing of data;neural video compression based on SURF scene change detection algorithm;cell detection in corneal endothelial images using directional filters;the method of probabilistic nodes combination in 2D information retrieval, pattern recognition and biometric modeling;3-D reconstruction of real objects using an android device;methods of natural image preprocessing supporting the automatic text recognition using the OCR algorithms;fast machine vision line detection for mobile robot navigation in dark environments;adjustment of viterbi algorithm for line following robots;studentized range for spatio-temporal track-before-detect algorithm;real-time US image enhancement by forward-backward diffusion using GPU;face-based distributed visitor identification system;color space optimization for lacunarity method in analysis of papanicolaou smears and toward texture-based 3D level set image segmentation.

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Bibliometric Analysis of Road Distress Detection Based on Citespace 24

Bibliometric Analysis of Road Distress Detection Based on Ci...

引用

5th International conference on Computer Science and Management Technology, ICCSMT 2024

作者： Li, Yaoye Zhang, Yinbo He, Rong Ma, Lianxia Chen, Fang Xinjiang communications Construction Group Co. Ltd. Xinjiang Urumqi China Xinjiang Key Laboratory of Transportation Prefabricated Construction and Maintenance Xinjiang Urumqi China Xinjiang University Xinjiang Urumqi China

ISBN: (纸本)9798400709999

To analyze the research progress in the field of road disease detection, this article searched the Web of Science Core Collection database for papers related to road disease detection from 2000 to *** CiteSpace software, a visual analysis was conducted on the 247 retrieved documents, focusing on annual publication numbers, publishing countries, core institutions and authors, keywords, burst words, and timeline mapping to explore the current status and trends in this *** findings indicate that since 2004, the overall research trend in road disease detection has been on an upward trajectory, with a notable increase in the number of research papers published in 2021, reflecting a significant surge in research ***, China, the United States, and Italy have been the most prolific in research *** leading research institutions are primarily scientific and technological academies, with Chang'an University taking a dominant position in the field of road disease *** keyword co-occurrence analysis, burst detection, and keyword clustering analysis, it was determined that disease detection technology, deep learning and machine learning, image processing and intelligent analysis, and system integration and development have been the research hotspots in the road disease detection field from 2000 to *** is anticipated that future research will evolve towards the directions of performance evaluation, multimodal data fusion, and real-time monitoring and analysis. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data fusion

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3rd International conference on Computing and Communication Networks, ICCCN 2023

3rd International Conference on Computing and Communication ...

引用

3rd International conference on Computing and Communication Networks, ICCCN 2023

ISBN: (纸本)9789819726707

The proceedings contain 60 papers. The special focus in this conference is on Computing and Communication Networks. The topics include: Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes;TSFTO: A Two-Stage Fuzzy-Based Tasks Orchestration Algorithm for Edge and Fog Computing Environments;tracking Climatic Variations Through Smart IoT-Driven Approach: An Exploratory Analysis;Design and Manufacturing of an Efficient Low-Cost Fire Surveillance System Based on GSM communications and IoT Technology;a Comparative Analysis of Optimized Routing Protocols for High-Performance Mobile Ad Hoc Networks;integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks;the Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks;Using Wireless Sensor Network Performance and Optimizing in Underground Mines with Virtual MIMO Antenna;a Novel Logistic Regression-Based Fire Detection Model Using IoT in Underground Coal Mines;An MQTT IoT Intrusion Detection System Using Deep-Learning;multi-objective Optimal Feature Selection for Cyber Security Integrated with Deep Learning;application of Gradient Boosting Classifier-Based Computational Intelligence to Detect Drug Addiction Threat in Society;insurance 4.0: Smart Insurance Technologies and Challenges Ahead;review on Vision Transformer for Satellite image Classification;primitive Roots and Euler Totient Function-Based Progressive visual Cryptography;approach for Fire Detection Using image processing;review of Various Approaches for Authorship Identification in Digital Forensics;machine Learning Model for Traffic Prediction and Pattern Extraction in High-Speed Optical Networks;improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.

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Improving Student Stress Analysis: Novel Methods for Collecting, Preprocessing, and Fusing Features 3rd

Improving Student Stress Analysis: Novel Methods for Collect...

引用

3rd International conference on Advancements in Smart Computing and Information Security, ASCIS 2024

作者： Bhatt, Zankhana Dobariya, Ashwin Faculty of Computer Application Marwadi University Gujarat Rajkot India

ISBN: (纸本)9783031862984

Due to the adverse effects of stress on students’ health and academic success, it is to create an effective method for stress detection. This study is used to predict student stress by combining biosignal data with image processing techniques. Employs various image pre processing of facial images in this research like Gaussian Blur, Median Blur, Bilateral Filters, and Canny edge detection to enhance the extraction of features. The Multi-task Cascaded Convolutional Neural Network (MTCNN) detects and aligns facia landmarks for precise data collection. Wearable device data on respiration, oxygen, temperature, and heart rate is combined with previously processed images. The robust dataset from physiological and visual characteristics may benefit future stress prediction machine learning applications. This comprehensive real-time stress detection method allows the development of customized interventions to improve student health and academic performance. The author is developing new artificial minority oversampling methods and improving machine learning models. The list includes KNN, Decision Trees, Random Forests, and XG Boost. The author has achieved accuracy rates and F1-macro score over 90% with KNN and SVM and expects even better results with other supervised machine learning algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biosignals Data Acquisition Face Alignment Facial Landmarks image Preprocessing MTCNN

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ViT-PQC: Vision Transformer-Based Patch Quality Controller for Edge-Assisted visual-SLAM

ViT-PQC: Vision Transformer-Based Patch Quality Controller f...

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Consumer communications and Networking conference, CCNC IEEE

作者： Yuma Katsuki Hayato Itsumi Yusuke Shinohara Koichi Nihei Anan Sawabe Takanori Iwai Secure System Platform Research Laboratories NEC Corporation Kawasaki Kanagawa Japan

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

Edge-based visual simultaneous localization and mapping (visual-SLAM) enables real-time indoor localization of robots by using substantial computing resources of an edge server. However, this system can place a burden on resource-constrained wireless networks because robots transmit their video data to the edge server via wireless networks. Given the sharing of the limited network capacity among multiple devices, the video bitrate needs to be reduced so as not to overshoot the available bandwidth. Although lowering the video quality can reduce the video bitrate, it also results in a loss of detailed image features and can negatively impact localization accuracy. In this paper, we propose a Vision Transformer-based patch quality controller (ViT-PQC) that reduces the video bitrate below the available bandwidth while preserving localization accuracy. ViT-PQC segments the video frame into patches and assigns an optimal image quality to each patch by taking into account both the image features of the recent frame and time shift features between the two most recent frames. Evaluation results demonstrate that ViT-PQC reduces the number of bitrate overshoots by 94% while preserving localization accuracy.

关键词： Location awareness visualization Accuracy Wireless networks image edge detection Bit rate Bandwidth Streaming media Transformers Video recording

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Enhanced Satellite image Fusion Using Deep Learning and Feature Extraction Techniques: A Survey 1st

Enhanced Satellite Image Fusion Using Deep Learning and Feat...

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1st International conference on Intelligent Systems in Computing and communications, ISCComm 2023

作者： Nallagachu, Swathi Sandanalakshmi, R. Department of Electronics and Communication Engineering Puducherry Technological University Puducherry India

ISBN: (纸本)9783031756047

This paper presents an overview and analysis of numerous research projects on image fusion methods, with a particular emphasis on deep learning-based methods. The research analyses the inadequacies of current fusion models and suggests novel methods for feature extraction, visual sensor networks, remote sensing applications, medical imaging, and multi-resolution image fusion. The study demonstrates the advantages of deep learning techniques for image fusion tasks, including Convolutional Neural Networks (CNNs), Stacked Auto encoders, and Convolutional Sparse Representation (CSR). These methods provide better fusion quality, fast processing, and better visual perception. Numerous studies provide novel methods, such as the rapid Integer Lifting Wavelet Transform (ILWT), Dual-Tree Complex Contourlet Transform (DT-CCT), and hybrid fusion methods that combine Discrete Cosine Transform (DCT) and Integer Lifting Wavelet Transform (ILWT) techniques. The review literature survey shows how these techniques can improve fusion outcomes while introducing little information distortion. In general, this paper brings together improvements in feature extraction and image fusion techniques, demonstrating the strength and potential of deep learning-based approaches. It is a useful tool for academics and professionals working in various fields who want to comprehend and advance these fields of study. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： image fusion

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