Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression MethodRead the full article
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Improved Cluster Intelligent and Complex Optimization Algorithm for Power Equipment CAD-Assisted Intelligent Operation and Maintenance
By using the data collected by the cluster intelligent and complex optimization of the power system equipment, the cluster intelligent and complex optimization algorithms are introduced into the CAD-aided intelligent operation and maintenance of power system equipment (CAD-IOMPSE). Based on this, the CAD-aided intelligent operation and maintenance graph of power system equipment is used to apply the cluster intelligent complex data contained in the quality inspection of the different types of data obtained to restrict the relationship between different entities for the value of knowledge contained in the collected power data in the operation process and control stage of the power system. According to the types of equipment with problems in the operation of power system, the defects and problems are quickly diagnosed to quickly locate the problems and give solutions. Finally, the results of example analysis show that compared with the traditional naming entity recognition algorithm, BiLSTM-softmax and Seq2Seq-Attention model, the algorithm in this study is better than the traditional algorithm in the three evaluation index values of accuracy, recall, and F1 value.
Automatic Rock Classification Algorithm Based on Ensemble Residual Network and Merged Region Extraction
Lithology identification of rocks is an important part in the field of oil and gas exploration, mineral exploration, and geological analysis. How to accomplish rock classification is a key issue for the further development of the geology industry. The current main method for classifying rock pictures containing background is to select sample points or disregard the disturbance of the background. For more accurate classification, the rock part extraction method for rock images containing boundaries is designed to eliminate the influence of background. First, the rock parts are extracted based on the image gradient information and color information, respectively. Then, the two images are intersected to realize the refinement of pixel-level information to obtain a pure rock image. Ensemble ResNet18 (ERN18) is designed as an image classification model. It contains basic blocks to reduce the loss of features during the training process. The method breaks the neglect of most previous studies on background interference. The effect of misclassification in certain regions on the results is eliminated by ensemble learning based on the voting method. The classification results are further improved. Compared with the effects of LeNet, AlexNet, and ResNet, ERN18 has achieved significant results.
The Interactive Design of Library Information Sharing in View of Network Communication Technology
From the perspective of data viewing, interactive design is to present abstract information and data in a visual form through a computer interface. It is formulated based on a humanized and flexible human-computer interaction model. The interaction process between computers and humans requires careful thinking and design. It must follow the principle of “user first, machine second.” Understanding the audience’s psychology and behavior characteristics can effectively enhance computer vision interaction and expand the scope of the audience. The research in this study aimed at the interactive design of library information sharing based on network communication technology. It introduces the organizational structure of the library and analyzes in detail the problems that the current library information resource sharing still faces. Then, this study proposes a dynamic differentiated service mechanism of DDSM to improve the success rate of information transmission in the interactive design system. This study designs an experiment on the interactive design of library information sharing by multiple types of users. The results of the experiment show that students of all grades and teachers use the library and library websites more frequently. For the interactive information service of the library, users are most satisfied with the project attitude of the book recommendation service method. Its satisfaction rate reaches 68%, and it is also the most popular among users. The main purpose of the interaction between library users is to share knowledge. However, the current domestic academic libraries have a general sense of interactive information services, and the development speed has always been slower than that in foreign countries.
CAD Interior Design Color Transfer Simulation Based on the Topological Information Area Matching Model
With the continuous development of social economy, interior design has gradually become an important content pursued by people, especially the rise of European and American style, industrial style, and other design styles, which have a greater impact on the style of interior design. In view of these needs and limitations, a topological information area matching model is introduced by trial in this study. The relationship of area matching is defined by trial through combining the business analysis flow of interior design, accurately controlling the importance of color transfer, and effectively performing the effective transfer of coloring according to the matching area, to improve the integrity of the color transfer, reduce the influence of the variegation in the color transfer on the result according to the mutually harmonious color method, and significantly improve the mutual harmony of colors. The simulation experiment results show that the topological information area matching model is effective, can ensure the true color of the image color, can be effectively adjusted according to the local matching relationship and color, and can support the simulation of CAD interior design color transfer.
The Improving Effect of Intelligent Speech Recognition System on English Learning
To improve the effect of English learning in the context of smart education, this study combines speech coding to improve the intelligent speech recognition algorithm, builds an intelligent English learning system, combines the characteristics of human ears, and studies a coding strategy of a psychoacoustic masking model based on the characteristics of human ears. Moreover, this study analyzes in detail the basic principles and implementation process of the psychoacoustic model coding strategy based on the characteristics of the human ear and completes the channel selection by calculating the masking threshold. In addition, this study verifies the effectiveness of the algorithm in this study through simulation experiments. Finally, this study builds a smart speech recognition system based on this model and uses simulation experiments to verify the effect of smart speech recognition on English learning. To improve the voice recognition effect of smart speech, band-pass filtering and envelope detection adopt the gammatone filter bank and Meddis inner hair cell model in the mathematical model of the cochlear system; at the same time, the masking effect model of psychoacoustics is introduced in the channel selection stage to prevent noise. Sex has been improved, and the recognition effect of smart voice has been improved. The analysis shows that the intelligent speech recognition system proposed in this study can effectively improve the effect of English learning. In particular, it has a great effect on improving the effect of oral learning.
Steel Plate Defect Recognition of Deep Neural Network Recognition Based on Space-Time Constraints
In order to improve the effect of real-time defect recognition in steel plate online production, this paper studies the method of steel plate defect recognition based on the deep neural network algorithm based on space-time constraints. Moreover, this paper improves the space-time constraint algorithm, optimizes the encryption structure of the traditional ABE scheme, and obtains a neural network feature recognition method based on space-time constraints. In order to process the massive image data stream generated instantaneously and ensure the real-time performance, accuracy, and stability of the detection system, this paper constructs a distributed parallel computing system structure based on the client/server (CC/S) model to obtain an intelligent recognition system. Through experimental research, it can be seen that the deep neural network recognition system based on space-time constraints proposed in this paper has a good effect in the recognition of steel plate defects.