Deformation modulus of rock mass has a significant role in the support design of an underground excavation. It is determined by expensive in-situ tests or by empirical models. Existing models for estimation of deformation modulus do not consider its stress dependence. Herein, data from several sources is used to develop a stress- (depth-) dependent relation for estimation of deformation modulus...

the method expressed by salem and ravat. (2003) for depth estimation of magnetic sources is used on gravity anomalies for the first time. the depth of some rectangular prisms as synthetic models are estimated through the method. the gravity effect of these models is also considered with a relatively high value of random noise. a field example is also included and the depth of the main anomaly h...

Abstract In this paper, we propose to work in the 2.5D space of scene facilitate composition new spherical panoramas. For adding depths panoramas, extend an existing method that was designed estimate relative from a single perspective image through user interaction. We analyze difficulties interactively provide such depth information for three different types presentation. Then, set basic tools...

Monocular depth estimation is the basic task in computer vision. Its accuracy has tremendous improvement decade with development of deep learning. However, blurry boundary map a serious problem. Researchers find that mainly caused by two factors. First, low-level features, containing and structure information, may be lost networks during convolution process. Second, model ignores errors introdu...

We review solutions to the problem of depth estimation, arguably most important subtask in scene understanding. focus on single image estimation problem. Due its properties, is currently best tackled with machine learning methods, successfully convolutional neural networks. provide an overview field by examining key works. examine non-deep approaches that mostly predate deep and utilize hand-cr...