Fractional calculus is used in computer vision for enhancement, better detection selectivity, developing robust denoising models, and dealing with discontinuities. Unlike integer-order derivatives, the non-local nature of fractional derivatives helps in gathering past and surrounding information.
Jun 7, 2022
Jun 7, 2022 · It briefly introduces the basics and presents applications of the fractional calculus in six different domains viz. edge detection, optical flow ...
edge detection, optical flow, image segmentation, image de-noising, image recognition, and object detection. The fractional derivatives ensure noise resilience ...
TL;DR: Fractional calculus is an abstract idea exploring interpretations of differentiation having non-integer order as mentioned in this paper and it has ...
It briefly introduces the basics and presents applications of the fractional calculus in six different domains viz. edge detection, optical flow, image ...
Applications of fractional calculus in computer vision: A survey. Sugandha Arora a,⇑, Trilok Mathur a, Shivi Agarwal a, Kamlesh Tiwari a, Phalguni Gupta b a
This paper presents a survey of fractional calculus neural network-based (FC NN-based) computer vision techniques for denoising, enhancement, object detection, ...
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Applications of fractional calculus in computer vision: A survey · List of references · Publications that cite this publication. Exploring stochastic dynamics ...
Jul 4, 2024 · This paper presents a survey of Fractional Calculus Neural Network-based (FC NN-based) computer vision techniques for denoising, enhancement, ...
Apr 25, 2023 · This paper reviews the use of fractional calculus in various artificial neural network architectures, such as radial basis functions, recurrent ...