Machine Learning Models: Using algorithms like neural networks and random forests, these models train prediction models from large samples of match data, gradually improving accuracy. This shift marks ...

A novel enhanced RIME algorithm (ERIME), incorporating selective evolutionary crossover and Gaussian random walk mechanisms, is proposed for the parameter estimation framework. Initially, a ...

Implementation of Algorithms for estimating the defocus map from a single defocused image source using image processing techniques and mathematical modelling.

Compared to ZoeDepth, a newly suggested metric depth model, the final model, DMD (Diffusion for Metric Depth), works better. DMD is a straightforward approach to zero-shot metric depth estimation on ...

In this paper, we propose a monocular catadioptric panoramic depth estimation algorithm based on an improved end-to-end neural network model. First, we use an enhanced concentric circle approximation ...

The proposed system involves the utilization of machine vision using YOLO for object detection, followed by the computation of the lens optic algorithms to calculate the distance. Results demonstrated ...

We present a fast penetration depth estimation algorithm between deformable polyhedral objects. We assume the continuum of non-rigid models are discretized using standard techniques, such as finite ...

In this paper, in order to tackle these problems, an improved unsupervised monocular depth estimation method for the ill-posed region is proposed through cascading training depth estimation network ...