A Novel Method of Multimodal Medical Image Fusion Based on Hybrid Approach of NSCT and DTCWT

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2022, Номер 18(03), С. 114 - 133

Опубликована: Март 8, 2022

The approach of multimodal medical image fusion, which extracts complementary information from several multimodality pictures, is one the most significant and beneficial illness study tools. This work proposed an effective strategy for picture fusion based on a hybrid NSCT DTCWT. experimental study's input images included computed tomography (CT), magnetic resonance imaging (MRI), positron emission (PET). A suggested employs convolutional network to generate weight map that incorporates pixel movement dual or more pictures. To provide greater visual comprehension by humans, method performed multiscale basis using pyramids. Additionally, local comparison-based employed adaptively alter mode decomposed coefficients. methodologies result in highest-quality fused lowest processing period, finest visualization terms quality objective assessment standards.

Язык: Английский

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Dark Web Illegal Activities Crawling and Classifying Using Data Mining Techniques

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2022, Номер 16(10), С. 122 - 139

Опубликована: Май 24, 2022

Dark web is a canopy concept that denotes any kind of illicit activities carried out by anonymous persons or organizations, thereby making it difficult to trace. The content on the dark constantly updated and changed. collection classification such illegal are challenging tasks, as they time-consuming. This problem has in recent times emerged an issue requires quick attention from both industry academia. To this end, efforts have been made article crawler capable collecting pages, cleaning them, saving them document database, proposed. carries automatic gathered pages into five classes. classifiers used classifying include Linear Support Vector Classifier (SVC), Naïve Bayes (NB), Document Frequency (TF-IDF). experimental results revealed accuracy rate 92% 81% were achieved SVC NB, respectively.

Язык: Английский

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Encryption of Color Image Based on DNA Strand and Exponential Factor

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2022, Номер 18(03), С. 101 - 113

Опубликована: Март 8, 2022

— In this study, a new method has been eliciting for encoding 2D and 3D color images. The DNA strand construction was used as the basis structuring method. This consisted of two main stages, encryption decryption stages. As each stage includes several operations to reach desired goal. coding stage, special table prepared show mechanism work. It starts with bases into binary orders, then zeros are added string finally consist four bits whose size is parallel representation set hexadecimal numbers represented in binary, where XOR operation done between values be result completely different from original code. Then we obtained converted decimal that placed an array same image encoded. Finally, last processed exponential function factor, so final 100% encoded image. decoding another algorithm built reflects work what preceded it exact copy worth noting standard images sizes were testing performance evaluation calculated based on factors: MSE, peak PSNR, time required perform process. achieved good results when compared other methods terms quality time.

Язык: Английский

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Security Risks of the Metaverse World

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2022, Номер 16(13), С. 4 - 14

Опубликована: Июль 11, 2022

An interesting paradigm is a metaverse which represents the next generation of using internet to improve human lives and provide new way communicate by building system that let user represented their avatar work, socialize play virtually integrating multiple technologies such as blockchain, artificial intelligence well virtual augmented reality. However, this may preserve many problems related security privacy starting from data breaches identity theft, in paper an overview world architecture connects real discuss main risks within Metaverse

Язык: Английский

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Face Patterns Analysis and Recognition System Based on Quantum Neural Network QNN

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2022, Номер 16(08), С. 34 - 48

Опубликована: Апрель 26, 2022

The past few years have witnessed a huge increase in the application of facial recognition, detection, and analysis technology. However, face recognition systems remain most popular among general public. system can detect presence when exposed to one. accuracy fairness that be derived from such necessitate their use, because humans, particularly security personnel tired target wrong person as suspect. artificial intelligence are properly trained capable efficiently identifying classifying faces without errors. In this work, use Matlab language was employed building software is recognizing differentiating different patterns. proposed equipped with camera serves practical aspect captures shots sent theoretical part special program designed recognize by comparing them database stored within program. work involved Quantum Neural Network. training dataset made up features vectors were obtained well-known set images people. Here, Principle Component Analysis (PCA) used for extraction feature then prepared next step. experimental results revealed efficient achieved through well-trained

Язык: Английский

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MCSC-Net: COVID-19 detection using deep-Q-neural network classification with RFNN-based hybrid whale optimization

Journal of X-Ray Science and Technology, Год журнала: 2023, Номер 31(3), С. 483 - 509

Опубликована: Фев. 28, 2023

COVID-19 is the most dangerous virus, and its accurate diagnosis saves lives slows spread. However, takes time requires trained professionals. Therefore, developing a deep learning (DL) model on low-radiated imaging modalities like chest X-rays (CXRs) needed.The existing DL models failed to diagnose other lung diseases accurately. This study implements multi-class CXR segmentation classification network (MCSC-Net) detect using images.Initially, hybrid median bilateral filter (HMBF) applied images reduce image noise enhance infected regions. Then, skip connection-based residual network-50 (SC-ResNet50) used segment (localize) The features from CXRs are further extracted robust feature neural (RFNN). Since initial contain joint COVID-19, normal, pneumonia bacterial, viral properties, conventional methods fail separate class of each disease-based feature. To extract distinct class, RFNN includes disease-specific attention mechanism (DSFSAM). Furthermore, hunting nature Hybrid whale optimization algorithm (HWOA) select best in class. Finally, deep-Q-neural (DQNN) classifies into multiple disease classes.The proposed MCSC-Net shows enhanced accuracy 99.09% for 2-class, 99.16% 3-class, 99.25% 4-class compared state-of-art approaches.The enables conduct tasks applying with high accuracy. Thus, together gold-standard clinical laboratory tests, this new method promising be future practice evaluate patients.

Язык: Английский

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Design a system for an approved video copyright over cloud based on biometric iris and random walk generator using watermark technique

Periodicals of Engineering and Natural Sciences (PEN), Год журнала: 2021, Номер 10(1), С. 178 - 178

Опубликована: Дек. 30, 2021

Copyright is a tool for preventing anyone forged to copy an electronic work from another person and claim that referred him. Since the identity of always determined by his name biometrics, there concern handle this information, preserve copyright. In paper, new idea copyright technology used prove video copyright, using blind watermarking technique, ownership information hidden inside frames linear congruential generator (LCG) adapted locations vector features extracted biometric image owner instead watermark in Pseudo Noise sequences or any other feature extraction technique. When providing watermarked vector, statistical operation increase randomization state amplifier factors LCG function. provides random positions where owner's stored video. The proposed method not difficult execute can present adaptable imperceptibility robustness performance. output results show approach based on average PSNR embedded 50 around 47.5 dB while remains undetectable. MSSIM values with range (0.83 0.99).

Язык: Английский

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DR-LL Gan: Diabetic Retinopathy Lesions Synthesis using Generative Adversarial Network

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2022, Номер 18(03), С. 151 - 163

Опубликована: Март 8, 2022

— Diabetic Retinopathy (DR) is a serious consequence of diabetes that seriously impact on the eyes and leading cause blindness. If lesions in DR arise central portion fundus, they may result significant vision loss, which we refer to as Macular Edema (DME). Deep learning (DL) techniques are commonly used utilized ophthalmology for discriminative tasks such diabetic retinopathy or age-related macular degeneration (AMD) diagnosis. typically need huge picture data sets deep convolutional neural networks (DCNNs) training, it should be graded by human specialists. According international protocol, classified into five severity categories. However, improving grading model high generality needs quantity balanced training data, challenging obtain, especially at levels severity. Typical augmentation, many applications retinal image processing domain, difficulty access annotated datasets legal concerns about patient privacy limiting issues. As result, concept creating synthetic pictures indistinguishable from actual has garnered more attention. GANs have been certain an effective framework databases anatomically accurate fundus pictures. GANs, particular, increasing attention ophthalmology. this article, present loss-less generative adversarial network (DR-LL GAN) generate good resolution May adjusted include random information lesion. large-scale generated train lesion segmentation with appropriate augmentation. Our experiments evaluated IDRID MESSIDOR datasets, it's obtained discrimination loss 0.69374 generation 1.10438, well accuracy 0.9840 our tests. This might support optimization design computer-aided screening medical picture, thus diagnostic reliability clinical assessment future sophisticated technological healthcare.

Язык: Английский

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Automated Cheating Detection based on Video Surveillance in the Examination Classes

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2022, Номер 16(08), С. 124 - 137

Опубликована: Апрель 26, 2022

A major issue in the field of education is exam malpractice and other forms academic dishonesty, where efforts made towards assessment students are undercut. In order to address this menace, a cheating detection system has been proposed study. The can detect real-time. uses video surveillance monitor activities student during exams, especially abnormal behavior. development involved use three different techniques, with functions. first technique helps determining direction students’ heads when they move from their initial direction, which script. Some form involves peeping at scripts people writing same exam. Whenever observes deviation that exceeds set threshold, it classifies behavior as abnormal. second works movement student’s iris. It detects iris moves copy answers written documents like mobile phones, books, hands, summary papers. third used identifying contact between hands face, well for shared students, such sharing incriminating materials. When any these detected, an automatic alarm alerts authority about thereby minimizing error rate occur result manual monitoring.

Язык: Английский

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Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review

JMIR mhealth and uhealth, Год журнала: 2023, Номер 12, С. e44406 - e44406

Опубликована: Авг. 18, 2023

In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of technology detection diagnosis COVID-19 has been subject numerous investigations, although thorough analysis prevention conducted using apps, creating a gap.

Язык: Английский

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