Research of the Defects in Anesthetic Masks

Laucka, Andrius; Andriukaitis, Darius

doi:10.13164/re.2015.1033

Cited by 12 publications

(7 citation statements)

References 15 publications

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“…People can get their emotions directly through facial expressions. In addition, automatic facial expression analysis has been widely applied in social robots [2]- [5], medical treatment [6], driver fatigue monitoring [7]- [9], and many other human-computer interaction systems [10]- [13], and facial expression recognition has a very important research value.…”

Section: Introductionmentioning

confidence: 99%

A Novel Fuzzy Optimized CNN-RNN Method for Facial Expression Recognition

Zhang

Tian

2021

ELEKTRON ELEKTROTECH

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Facial expression is one of the important ways of transferring emotion in interpersonal communication, and it has been widely used in many interpersonal communication systems. The traditional facial expression recognition methods are not intelligent enough to manage the model uncertainty. The deep learning method has obvious ability to deal with model uncertainty in the image recognition. The deep learning method is able to complete the facial expression work, but the recognition rate can be further improved by a hybrid learning strategy. In this paper, a Fuzzy optimized convolutional neural network-recurrent neural network (CNN-RNN) method for facial expression recognition is proposed to solve the problems of direct image convolution without image enhancement and simple convolution stack ignoring feature layer-by-layer convolution resulting in information loss. Firstly, each face image is scaled by the bilinear interpolation and the affine transformation is adopted to expand the image data to avoid the shortage of the data set. Then the feature map of the facial expression is extracted by the CNN with small information loss. To deal with the uncertainty in the feature map, the Fuzzy logic is employed to reduce the uncertainty by recognizing the highly nonlinear relationship between the features. Then the output of the Fuzzy model is fed with the RNN to classify different facial expression images. The recognition results based on the open datasets CK, Jaffe, and FER2013 show that the proposed Fuzzy optimized CNN-RNN method has a certain improvement in the recognition effect of different facial expression data sets compared with current popular algorithms.

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Section: Introductionmentioning

confidence: 99%

A Novel Fuzzy Optimized CNN-RNN Method for Facial Expression Recognition

Zhang

Tian

2021

ELEKTRON ELEKTROTECH

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“…Another exemplary defect detection system for plastic products, namely anaesthetic respiratory masks, based on computer vision, is presented in [ 12 ]. Recently, an interesting approach to optimization of tool paths during the 3D printing process was suggested by Fok et al [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Objective 3D Printed Surface Quality Assessment Based on Entropy of Depth Maps

Fastowicz

Grudziński

Tecław

et al. 2019

Entropy

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A rapid development and growing popularity of additive manufacturing technology leads to new challenging tasks allowing not only a reliable monitoring of the progress of the 3D printing process but also the quality of the printed objects. The automatic objective assessment of the surface quality of the 3D printed objects proposed in the paper, which is based on the analysis of depth maps, allows for determining the quality of surfaces during printing for the devices equipped with the built-in 3D scanners. In the case of detected low quality, some corrections can be made or the printing process may be aborted to save the filament, time and energy. The application of the entropy analysis of the 3D scans allows evaluating the surface regularity independently on the color of the filament in contrast to many other possible methods based on the analysis of visible light images. The results obtained using the proposed approach are encouraging and further combination of the proposed approach with camera-based methods might be possible as well.

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“…It is not enough to provide production in series to quality control anymore. Volumes of quality production increase only by using continuous control and by checking every product [1].…”

Section: Introductionmentioning

confidence: 99%

Research of the Equipment Self-Calibration Methods for Different Shape Fertilizers Particles Distribution by Size Using Image Processing Measurement Method

2019

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The fourth digital revolution of industry makes substantive changes to the rate and methodology of work performance. Machines and robots do the majority of work in robotized and automated factories, while people only supervise them. After an increase of production efficiency, quality control became a critical point. Therefore, quality control systems of computer visions are increasingly installed. The branch of chemical industry requires measurements of quality at as great a frequency as possible. Consequently, indirect measurements are effectively used at this point. This research presents the method of indirect particle measurement. Particles are measured using digital image processing. The algorithm is used for particle measurement to automatically adjust the measurement results. Numerical intelligence is added to the algorithm to increase the accuracy of correction results. The research deals with the problem of matching the results of indirect measurements and the results of the control equipment. For data analysis, fertilizer diameter, mean diameter, aspect ratio, symmetry, sphericity, convexity and some other parameters are used. The mismatch of the artificial neural network results with the control equipment results is slightly higher than 1%.

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Research of the Defects in Anesthetic Masks

Cited by 12 publications

References 15 publications

A Novel Fuzzy Optimized CNN-RNN Method for Facial Expression Recognition

A Novel Fuzzy Optimized CNN-RNN Method for Facial Expression Recognition

Objective 3D Printed Surface Quality Assessment Based on Entropy of Depth Maps

Research of the Equipment Self-Calibration Methods for Different Shape Fertilizers Particles Distribution by Size Using Image Processing Measurement Method

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