Fruit classification is a computer vision task that aims to classify fruit classes correctly, given an image. Nearly all studies have used RGB color images as inputs, few costly hyperspectral images, and classical ML-based colorized depth images. Depth apparent benefits such invariance lighting, less storage requirement, better foreground-background separation, more pronounced curvature details...

background and aims. radiography is used to diagnose the demineralization process and carious lesions; however, conventional radiography and direct digital images do not show these lesions when the amount of demineralization is less than 40%. digital subtraction radiography has recently been used to improve the diagnostic quality of these lesions. the purpose of this study was to compare the ca...

In this paper, we propose a dense depth estimation pipeline for multiview 360∘ images. The proposed leverages spherical camera model that compensates radial distortion in key contribution of paper is the extension to by introducing translation scaling scheme. Moreover, an effective method setting virtual and minimizing photonic reprojection error. We validate performance using images natural sc...

A method is developed for the computation of depth maps, modulo scale, from one single image of a polyhedral scene. Only aane shape properties of the scene and image are used, hence no metrical information. Results from simple experiments show good performance, both what concerns exactness and robustness. It is also shown how the underlying theory may be used to single out and characterise cert...

In this paper, we propose an efficient algorithm to reconstruct the 3D structure of a human face from one or more of its 2D images with different poses. In our algorithm, the nonlinear least-squares model is first employed to estimate the depth values of facial feature points and the pose of the 2D face image concerned by means of the similarity transform. Furthermore, different optimization sc...