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Feature selection algorithms are crucial technologies for reducing the dimensionality of high-dimensional data. However, the exponential expansion of the decision space due to high-dimensional data makes most feature selection algorithms highly ...

• Proposed a dynamic multi-swarm construction mechanism based on centroid distance.
• An elite tuning strategy to address invalid probability flips is proposed.
• Dynamic multi-swarm whale optimization algorithm based on elite tuning is ...

In this paper, we address the problem of personalized gaze estimation. Due to the anatomical differences between individuals, current personalized gaze models often rely on fine-tuning or fully-supervised methods with labeled calibration samples, which ...

In queueing systems where queues are invisible, it is critical for companies to make decisions about the timing of announcing the anticipated delay to customers. In this paper, a simulation model is built to simulate an invisible queueing system, and ...

Feature selection is a key technique for data dimensionality reduction, and there are many challenges in facing the exponential expansion phenomenon of high-dimensional decision space. In order to improve the quality of feature selection, we ...

• Proposed quadratic interpolation mechanism with memory information interaction.
• A reverse correction mechanism is proposed to resolve invalid probability flips.
• An improved discrete whale optimization algorithm is proposed.
• The ...

We consider the problem of user-adaptive 3D gaze estimation. The performance of person-independent gaze estimation is limited due to interpersonal anatomical differences. Our goal is to provide a personalized gaze estimation model specifically adapted to ...

In order to understand the development of sports culture, a data mining based analysis study on the development of sports culture has been proposed. This paper first analyzes the significance of combining data mining with sports culture. Secondly, the ...

To efficiently manage information security, firms typically outsource the security of partial business (core and non-core) to a managed security service provider (MSSP). Four options can be adopted for a firm on security strategy, that is, all ...

• Performance of object detection tends to degrade on low-quality images.
• Choosing suitable enhancement algorithms can improve the detection performance.
• Reinforcement learning can autonomously select algorithms based on the ...

The task of object detection for low-quality images in multiple scenarios remains a challenging task. To alleviate this problem, a novel approach to improve the detection performance of the model on low-quality images using deep reinforcement ...

Approximate multipliers (AMs) have widely been investigated to pursue high-performance and energy-efficient hardware designs for error-tolerant applications, such as neural networks (NNs). The computing accuracy of an AM has been evaluated by using ...

Text-based person search aims to retrieve pedestrian images corresponding to a specific identity based on a textual description. Existing methods primarily focus on either the alignment of global features through well-designed loss functions or ...

The evolution of critical care medicine and nursing has aided and enabled the rescue of a large number of patients from numerous life-threatening diseases. However, in many cases, patient health may not be quickly restored, and the long-...

To efficiently manage information security, firms typically allocate limited budgets to protect their information assets based on asset types and hacker types. This paper builds a game-theoretical model to discuss the strategic interaction ...

Image retrieval is an important task in computer vision. Among various image retrieval approaches, deep hashing methods map input images to binary codes for nearest neighbor search, achieving advantages in both search time and space. In recent years, ...

Network embedding has facilitated lots of network analytical tasks by representing nodes as low-dimensional vectors. As an extension of convolutional neural networks from Euclidean data to irregular data, Graph Convolutional Networks (GCNs) ...

Intelligent internet of things (IIoTs) have these features: heterogeneous network patterns, significant differences in devices, dynamic variability of network topologies, etc. In the complex security situation, it is necessary to reject data from ...

• We propose a VFNet for semi-supervised saliency prediction in omnidirectional images (ODIs).

Compared with the annotated data for the 2D image saliency prediction task, the annotated data for training omnidirectional image (or 360° image) saliency prediction models are not sufficient. Most existing fully-supervised saliency ...

Transcription factors (TFs) play a part in gene expression. TFs can form complex gene expression regulation system by combining with DNA. Thereby, identifying the binding regions has become an indispensable step for understanding the regulatory mechanism ...

Given a face image, most of previous works in gaze estimation infer the gaze via a well-trained model with supervised training. However, the distribution of test data may be very different compared to that of training data since samples might be corrupted ...

Lane boundaries, as the main component of high definition maps (HD maps), are difficult to auto-generate accurately in various scenarios. In this paper, a general lane boundary extraction method is proposed for HD mapping in both highway and urban ...

Information resources have been shared to promote the business operations of firms. However, the connection of business information sharing interfaces between firms has increased the attack surface and created opportunities for the hacker. We examine the ...