Abstract: The multicriterion problem of integer optimization is examined. Developed and proved exact and approximate algorithms, which are the extensions of gradient methods for vector integer ...

Abstract: Infrared small target detection (IRSTD) is challenging due to low target-background contrast and small target size, leading to missed detections and false alarms (Fas). To address these ...

The cost function in several machine learning algorithms is minimized using the optimization approach gradient descent. Its primary objective is to update the parameters of a learning algorithm. These ...

The main objective of this study is to compare face recognition accuracies in the case when the grey levels in each pixel of the face images are replaced by the gradient and the surface normal vectors ...

This paper covers the concept of a conservative vector field, and its application in vector physics and Newtonian mechanics. Conservative vector fields are defined as the gradient of a scalar-valued ...

A subset of the true optical flow can be extracted by constructing a vector field that represents image gradients and then tracking vectors in this vector field. This pseudo-flow (p-flow) subset ...

Gradient Descent is an optimization algorithm used primarily in machine learning and statistics to minimize a function, typically a loss or cost function in the context of machine learning models. The ...