Design, simulation and comparative analysis of carbon nanotube based energy efficient priority encoders for nanoelectronic applications

Khan, Imran Ahmed; Rai, Amrita; Keshari, J. P.; Nizamuddin, M.; Nayak, Seema; Sharma, Dheeraj

doi:10.1016/j.prime.2023.100138

Cited by 2 publications

(1 citation statement)

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“…An extended super-resolution GAN (ESRGAN) model, which is based on generative adversarial networks (GANs), shown outstanding picture enhancing capabilities, yet high-frequency edge information, is typically lost in reconstructed images (Rabi et al, 2020;Alkishri et al, 2024). A framework is suggested that combines Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) in an optimal manner, aiming to achieve high-accuracy ship recognition from low-resolution satellite photos (Khan, & Singh, 2023). This approach not only enhances image quality but also reduces training time, as outlined in reference (Pushkar et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Improving Digital Satellite Image for security purposes

Hamdan Ali

2024

AIRDJ

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Satellite imagery is employed in many different fields of study. These pictures have serious quality problems. Image enhancement algorithms, however, can improve it in terms of contrast, brightness, feature elimination from noise contents, etc. These algorithms present and analyse the picture's properties by sharpening, focusing, or smoothing the image. Therefore, the specific application determines the goal of picture enhancement. This paper briefly overviews picture enhancement methods that produce optimal and progressive outcomes for satellite images used for secured remote sensing. To do this, various image enhancement techniques are used, which are widely used today to improve image quality across various image processing applications. Some commonly used image enhancement techniques include spatial filtering, contrast stretching, and histogram equalisation. These techniques aim to enhance the visual quality of satellite images by adjusting brightness and contrast and reducing noise. These methods can also improve the interpretability of the images for remote sensing purposes. The enhancement of satellite images finds use in several fields, particularly security. It is essential for security applications, including threat detection, border control, and surveillance. Security professionals may more effectively analyse and understand data to spot any dangers or questionable activity by boosting the visual details and general quality. Keywords: Satellite image analysis; mean filter; secured application; SVM; wavelet transformation

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Section: Introductionmentioning

confidence: 99%