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Modelling of high-dimension chaotic, noisy, and non-stationary time series of complex fractal dynamics is a big challenge. In this research work, a novel approach of Leverage Convolution LC ARFIMA– GARCH model is presented for sequential learning ...

Automatic segmentation of shoulder muscle MRI is challenging due to the high variation in muscle size, shape, texture, and spatial position of tears. Manual segmentation of tear and muscle portion is hard, time-consuming, and subjective to ...

The new emerging COVID-19, declared a pandemic disease, has affected millions of human lives and caused a massive burden on healthcare centers. Therefore, a quick, accurate, and low-cost computer-based tool is required to timely detect ...

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• Two new frameworks, named as DHL and DBHL are proposed for COVID-19 detection in chest X-ray images.

Smart grid systems enhanced the capability of traditional power networks while being vulnerable to different types of cyber‐attacks. These vulnerabilities could cause attackers to crash into the network breaching the integrity and confidentiality ...

This article proposes a feature‐based IDS for smart grid systems. The proposed system performance is evaluated in terms of accuracy, intrusion detection rate (DR), and false alarm rate (FAR). The obtained results show that the random forest and neural ...

Irrelevant and redundant features increase the computation and storage requirements, and the extraction of required information becomes challenging. Feature selection enables us to extract the useful information from the given data. Streaming feature ...

• A novel approach comprised of fuzzy intelligence and GMM has been proposed for segmentation of brain MRI and carotid artery ultrasound images.

In medical image analysis for disease diagnosis, segmentation is one of the challenging tasks. Owing to the inherited degradations in MRI improper segments are produced. Segmentation process is an ...

A new robust fundus vessel tracking technique has been proposed.The proposed technique tackles the challenging problem of blood vessels network detection in human retinal image.Challenging occlusion problem has been resolved by incorporating of Hidden ...

In this paper, a robust method is proposed for segmentation of medical images by exploiting the concept of information gain. Medical images contain inherent noise due to imaging equipment, operating environment and patient movement during image ...

In this paper, we present a hybrid, image restoration approach. The proposed approach combines the geostatistical interpolation of punctual kriging, artificial neural networks (ANNs), and fuzzy logic based approaches. Images degraded with Gaussian white ...

Disease diagnosis based on ultrasound imaging is popular because of its non-invasive nature. However, ultrasound imaging system produces low quality images due to the presence of spackle noise and wave interferences. This shortcoming requires a ...

Image segmentation plays vital role in computer vision, pattern recognition, disease diagnosing in medical images and many other fields. Medical image segmentation is one of the most attractive areas of research, because successfulness of the post-...