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In this study, we propose a two-stage method for material segmentation in hyperspectral images. The first stage employs a Convolutional Neural Network (CNN) to predict the material label at individual pixels. The second stage further refines the segmentation by a fully-connected Conditional Random Field (CRF) framework. For the first stage, we experimented with two different network architectures...
Intelligent robots and machines are becoming pervasive in human populated environments. A desirable capability of these agents is to respond to goal-oriented commands by autonomously constructing task plans. However, such autonomy can add significant cognitive load and potentially introduce safety risks to humans when agents behave in unexpected ways. Hence, for such agents to be helpful, one important...
Artificial intelligence technique namely artificial neural network (ANN) was used to describe the enzymatic kinetics of cellulose hydrolysis in a heterogeneous system, and compared with response surface methodology (RSM). Three hydrolysis conditions (activity of added cellulase, substrate concentration and time) served as the input of the neural network model, and the glucose content served as the...
The traditional prediction model is not able to achieve a satisfying prediction effect in the problem of a non-linear system and nonstationary financial signal. The existing wavelet neural network has overcome the deficiency of traditional prediction model which is limited to linear system when predicting. However, wavelet neural network has a defect of confusing signal frequency. Based on the theory...
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