Vision prehension with CBIR for cloud robo

Abstract

Content Based Image Retrieval is very hottest research area in computer vision and image processing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing research area. Neural Network is a grid of "neuron like" nodes, in this paper we follow towards Neural Network (NN), is committed to contributing a new technical concept for the scene understanding and recognition by consolidating new intellectual visual features into the scene expression, which can be very crucial and provide cognitive intelligence to cloud robot. Inspired by Artificial Neural Network intelligence due to its dynamic nature, we make use of the attributes of the Gabor filter and Laplacian of Gaussian filter which is to be akin to robot visual perception, and apply the wavelet transform to inspect a new approach in complex environment natural scene perception and understanding for virtual phenomena. Through the study of Neural Network, the perception ability of the natural scene image from complex environment for cloud robot is enhanced with the integration of cognitive visual features and the scene expression.

Partial Observer Decision Process Model for Crane-Robot Action

“…We retrieve the feature for decision using BN for the last N time steps and discriminate the class label of the Steps/count (10) Steps/count (50) forecasting result to decide whether to accept it accordingly. e structure of the model is shown in Figure 3.…”

“…is approach not only let the system proceed but also provide learning in natural scene with complex environmental perception and understanding. rough the study of perception ability of the natural scene image from complex environment, robot vision is enhanced with the integration of cognitive visual feature and the scene expression [10].…”

Toward analyzing the impact of healthcare treatments in industry 4.0 environment—a self-care case study during COVID-19 outbreak

“…Digitalized data now provide different enhancements to human organization work environments through torment figure and reconnaissance masses prosperity control and have affected individual idea progress. Similarly, enormous real factors can sustain movement, charge and risk markdown, and capability benefits [ 2 , 3 ]. Colossal records are useful, not handiest for slick adaptable prosperity (m-prosperity) exercises, at any rate besides for social protection adventures [ 4 , 5 ].…”

Contemporary Layout’s Integration for Geospatial Image Mining

“…Chakraborty et al [19] firstly estimated camera view point and position of the peoples in 3D scene then extraction spatial information from 3D people position. Neural network based a novel approach proposed by Khan et al [20] which contributes a novel technical concept for the scene understanding and recognition, which can be important to provide vision intelligence to cloud robot.…”