The automatic human facial emotion recognition (AHFER) system has its wide significant contribution in several disciplines, such as human-computer collaboration, human-robot interaction, and so on. Multiple research p...
The automatic human facial emotion recognition (AHFER) system has its wide significant contribution in several disciplines, such as human-computer collaboration, human-robot interaction, and so on. Multiple research projects have been conducted regarding this topic because it is a challenging and interesting task, especially in the area of computer vision. The purpose of the work is to recognize facial emotions using a depthwise separable convolutional neural network (DS-CNN). Apart from that, a facial emotion dataset has been proposed, and splitting functions, intensity normalization, image cropping, and grayscale conversion have been used in data pre-processing. The AHFER system is capable of recognizing four types of emotions: happy, sad, angry, and neutral. The results of the experiment showed that the AHFER method is 99 percent accurate when training and 93 percent accurate when validating. Additionally, we determined the confusion matrix with precision, recall, and fl-score. A comparison between the DS-CNN and DNN models was performed. The DS-CNN model performed significantly better than the DNN model. The DS-CNN model could be improved in the future by including more facial emotion categories.
The estimator has been constructed similar to the Parzen-Rosenblatt window method using a single realization of a Poisson process at a fixed time interval. The intensity function of a non-homogeneous Poisson process i...
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The article deals with the problem of managing an autonomous photovoltaic power station, which is a complex technical system characterized by high uncertainty of the initial information and control objectives. The pap...
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Currently computer vision-based controlsystems are widely used. In such systems, procedures for detecting specified objects in images, calculating their characteristics and generating information for decision making ...
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The article deals with the creation of intelligent tractor driver support systems based on computer vision technologies for analyzing the direction of movement and detecting obstacles when performing specified operati...
The article deals with the creation of intelligent tractor driver support systems based on computer vision technologies for analyzing the direction of movement and detecting obstacles when performing specified operations, such as plowing, harrowing, weeding, and fertilizing. Electric power poles, trees, rocks, bird nests, animals, people, and field roads are identified as obstacles. The solution of functional problems in the system is based on the extraction of information from images using methods for detecting and recognizing objects in images. The analysis of existing approaches to solving the problems under consideration is carried out and it is shown that the use of deep neural networks is effective. The practical use of the methods based on the chosen approach is based on the performance of the computing system, the availability of sufficient training data and the optimality of the training method. It is shown that these factors are important when implementing an intelligent tractor driver support system.
Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output ...
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ISBN:
(数字)9798331527471
ISBN:
(纸本)9798331527488
Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.
Today information systems are used in all spheres of human society. The main criterion for the optimal operation of an enterprise information system is complete automation. This is especially important when one needs ...
Today information systems are used in all spheres of human society. The main criterion for the optimal operation of an enterprise information system is complete automation. This is especially important when one needs to handle huge data streams. In this regard, the implementation of automatedcontrolsystems is urgently necessary. They significantly increase efficiency in all areas of production and improve employee productivity. In this case, it is necessary to pay special attention not only to the creation of a unified information environment, but also to the possibility of assessing the workload and functionality of its individual components. Such an opportunity is provided by the application of the foundations of constructing functional models of subsystems.
The article analyzes the use of the decision tree method. The analysis of flaws in a machine-building enterprise. The consideration of the reasons for the appearance of defects in the product as well as suggestions fo...
The article analyzes the use of the decision tree method. The analysis of flaws in a machine-building enterprise. The consideration of the reasons for the appearance of defects in the product as well as suggestions for making changes to the regulatory and technical documentation. At the moment, non-destructive diagnostic methods are widely used, which allow you to determine the location of faults and predict the state of the object without the need for research that requires the object to be taken out of operation or dismantled.
The paper describes an approach to the image borders detection that is based on the use of the weight model and the operation of the morphological gradient calculating. The proposed method relates to multiscale image ...
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A field programmable gate array (FPGA) has been configured to control the temperature average value and spatial uniformity of a TEM-cell. The system is composed of 24 Peltier elements (PE) and 52 temperature sensors (...
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