International Journal of Image, Graphics and Signal Processing最新文献_第3页

A Survey of Artificial Life and Nature-inspired Techniques in Computer Graphics and Visualization 计算机图形学和可视化中的人工生命和自然启发技术概览

International Journal of Image, Graphics and Signal Processing Pub Date : 2024-02-08 DOI: 10.5815/ijigsp.2024.01.01

Bushra Ferdousi, Tim Mc Graw

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Mask Region-based Convolution Neural Network (Mask R-CNN) Classification of Alzheimer’s Disease Based on Magnetic Resonance Imaging (MRI) 基于磁共振成像（MRI）的阿尔茨海默病掩膜区域卷积神经网络（Mask R-CNN）

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.05

Anil Kumar Pallikonda, P. S. Varma, B. Vivekanandam

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Radio Receiver with Internal Compression of Input Signals Using a Dispersive Delay Line with Bandpass Filters 利用带通滤波器的色散延迟线对输入信号进行内部压缩的无线电接收器

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.01

Roman Pantyeyev, Felix Yanovsky, Andriy Mykolushko, Volodymyr Shutko

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Modeling and Simulating Mutual Testing in Complex Systems by Using Petri Nets 利用 Petri 网建模和模拟复杂系统中的相互测试

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.07

V. Mashkov, V. Lytvynenko, I. Lurie

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Analytical and Computer Polarization-Correlation Processing of Brest Tumors’ Laser Fields for Cancer Detection 用于癌症检测的布雷斯特肿瘤激光场分析和计算机偏振相关处理技术

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.04

Yuriy Ushenko, Valentina Dvorzhak, Oleksandr Dubolazov, Oleksandr Ushenko, Ivan Mikirin, Zhengbing Hu

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Chilli Dryness and Ripening Stages Assessment Using Machine Vision 利用机器视觉评估辣椒的干燥和成熟阶段

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.06

M. Sajjan, Lingangouda Kulkarni, Basavaraj S. Anami, Nijagunadev B. Gaddagimath, Liset Sulay Rodriguez Baca

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Enhancement of Mammographic Images Based on Wavelet Denoise and Morphological Contrast Enhancement 基于小波去噪和形态对比度增强的乳腺 X 射线图像增强技术

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.03

Toan Le Van, Liet Van Dang

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A Novel GRU Based Encoder-Decoder Model (GRUED) Using Inverse Distance Weighted Interpolation for Air Quality Forecasting 基于 GRU 的新型编码器-解码器模型 (GRUED)，使用反距离加权插值法进行空气质量预测

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-12-08 DOI: 10.5815/ijigsp.2023.06.02

Tanya Garg, Daljeet Singh Bawa, Sumayya Khalid

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Real-Time Vehicle Detection for Surveillance of River Dredging Areas Using Convolutional Neural Networks 基于卷积神经网络的河道疏浚区实时车辆检测

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-10-08 DOI: 10.5815/ijigsp.2023.05.02

Mohammed Abduljabbar Zaid Al Bayati, Muhammet Çakmak

{"title":"Real-Time Vehicle Detection for Surveillance of River Dredging Areas Using Convolutional Neural Networks","authors":"Mohammed Abduljabbar Zaid Al Bayati, Muhammet Çakmak","doi":"10.5815/ijigsp.2023.05.02","DOIUrl":"https://doi.org/10.5815/ijigsp.2023.05.02","url":null,"abstract":"The presence of illegal activities such as illegitimate mining and sand theft in river dredging areas leads to economic losses. However, manual monitoring is expensive and time-consuming. Therefore, automated surveillance systems are preferred to mitigate such activities, as they are accurate and available at all times. In order to monitor river dredging areas, two essential steps for surveillance are vehicle detection and license plate recognition. Most current frameworks for vehicle detection employ plain feed-forward Convolutional Neural Networks (CNNs) as backbone architectures. However, these are scale-sensitive and cannot handle variations in vehicles' scales in consecutive video frames. To address these issues, Scale Invariant Hybrid Convolutional Neural Network (SIH-CNN) architecture is proposed for real-time vehicle detection in this study. The publicly available benchmark UA-DETRAC is used to validate the performance of the proposed architecture. Results show that the proposed SIH-CNN model achieved a mean average precision (mAP) of 77.76% on the UA-DETRAC benchmark, which is 3.94% higher than the baseline detector with real-time performance of 48.4 frames per seconds.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135252761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast Encryption Scheme for Secure Transmission of e-Healthcare Images 电子医疗影像安全传输的快速加密方案

International Journal of Image, Graphics and Signal Processing Pub Date : 2023-10-08 DOI: 10.5815/ijigsp.2023.05.07

Devisha Tiwari, Bhaskar Mondal, Anil Singh

{"title":"Fast Encryption Scheme for Secure Transmission of e-Healthcare Images","authors":"Devisha Tiwari, Bhaskar Mondal, Anil Singh","doi":"10.5815/ijigsp.2023.05.07","DOIUrl":"https://doi.org/10.5815/ijigsp.2023.05.07","url":null,"abstract":"E-healthcare systems (EHSD), medical communications, digital imaging (DICOM) things have gained popularity over the past decade as they have become the top contenders for interoperability and adoption as a global standard for transmitting and communicating medical data. Security is a growing issue as EHSD and DICOM have grown more usable on any-to-any devices. The goal of this research is to create a privacy-preserving encryption technique for EHSD rapid communication with minimal storage. A new 2D logistic-sine chaotic map (2DLSCM) is used to design the proposed encryption method, which has been developed specifically for peer-to-peer communications via unique keys. Through the 3D Lorenz map which feeds the initial values to it, the 2DLSCM is able to provide a unique keyspace of 2544 bits (2^544bits) in each go of peer-to-peer paired transmission. Permutation-diffusion design is used in the encryption process, and 2DLSCM with 3DLorenz system are used to generate unique initial values for the keys. Without interfering with real-time medical transmission, the approach can quickly encrypt any EHSD image and DICOM objects. To assess the method, five distinct EHSD images of different kinds, sizes, and quality are selected. The findings indicate strong protection, speed, and scalability when compared to existing similar methods in literature.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135252754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0