PRIS

The attention mechanism has been widely used and achieved good results in many visual tasks. But the calculations of attention mechanism in vision tasks consume huge spaces and times, which is the obvious disadvantage of this method. In order to ...

The task of reconstructing object shapes from input images has become increasingly important in various fields, such as computer vision, robotics, augmented reality, video games, and autonomous vehicles. While approaches for reconstructing shapes with ...

Traditional art exhibitions are usually dominated by relatively static displays such as text, pictures and common multimedia technology. Subject to technical limitations, the exhibition means are relatively simple and the content is relatively thin, ...

Lane detection has been one of the most important functions in the autonomous driving perception module. Most of the current research require complex post-processing and curve fitting processes before they can be used by subsequent regulation modules. ...

Transformer models have shown remarkable effectiveness in capturing long-range dependencies and extracting features for single image super-resolution. However, their deployment on edge devices is hindered by their high computational complexity. To ...

Object detection under one-level feature is a challenging task, which requires that object representations at different scales can be extracted on a single feature map. However, existing object detectors using a one-level feature suffer from inadequate ...

The use of multilingual models for natural language processing is becoming increasingly popular in industrial and business applications, particularly in multilingual societies. In this study, we investigate the transfer learning capabilities of ...

Reinforcement learning algorithms have been used to discover the strategies in game theory. This study investigates whether Q learning, one of the classic reinforcement learning methods, is capable of training bargaining players via self-play, a ...

To address the lack of development capacity of Runge Kutta Optimizer, we propose the Multi-population Runge Kutta algorithm Based on Gaussian disturbance(MPRUN). In the algorithm, the population is divided into subgroups. The individuals in the ...

The formal verification of the operating systems in power monitoring system is an important means to ensure the security of the operating system in power monitoring system. This paper introduces the verification principles and framework of formal ...

The line loss rate varies significantly among different substation areas due to diverse influencing factors. Consequently, a study is conducted to investigate the line loss index of a substation area by employing a cooperative game approach that ...

The multi-area economic dispatch (MAED) is a hot and vital research topic for energy saving and emission reduction. Multi-areal economic dispatch refers to the most economical distribution of load requirement among the output units under the premise of ...

In order to better monitor public opinion, this study reviews how the existing thesis work theoretically and practically from the interdisciplinary perspective of communication and computer science and then proposes a new vision under the framework of “...

For data streams, drift detection methods warn and detect the changes in patterns over time. For example, in smart manufacturing, many data streams are generated from sensors that monitor the real-time operation of manufacturing. Drift detection can be ...

With the continuous development of social economy, infrastructure such as highways and bridges continues to develop, and overloaded vehicles are repeatedly prohibited. Therefore, many places have set up "height limit gantry frames" at the entrances of ...

In response to the application requirements of identifying and classifying multiple types of fibers, this paper proposes a fiber recognition algorithm based on improved Mask RCNN to achieve recognition and classification of multiple types of fibers, ...

At present, data center security and energy consumption have been continuously concerned and discussed. There are some new technology to reduce energy consumption of data center, but few studies focus on make full use of the resources of the existing ...

Vehicle spare parts demand forecasting is crucial for optimizing inventory and improving maintenance efficiency. This study aims to explore a vehicle spare parts demand forecasting method based on the fusion of XGBoost and LightGBM models to enhance ...