We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modeling improvements, including Residual DCN, which adds attention and residual ...

Recently, graph-based deep learning models have exhibited remarkable performance in generating solution expressions for the math word problem (MWP). However, most of these models have not taken into account the limitations and errors in ...

This research explores the computational empowerment of intangible cultural heritage through interactive generative platforms. Prototypes in TouchDesigner software visualize traditional Kam minority patterns by applying particle system effects to ...

• An evaluation model is proposed by considering risk attitudes and aggregation method.
• Our distance entropy function reduces the inconsistent degree of evaluation results.
• Empirical example is performed to validate the applicability ...

Cross-efficiency evaluation with the data envelopment analysis (DEA) model is an effective way to assess performance and provide a complete ranking of decision-making units. However, it is generally assumed that decision makers are perfectly ...

With the improvement of service delay and quality requirements for new applications such as unmanned driving, internet of vehicles, and virtual reality, the deployment of network services is gradually moving from the cloud to the edge. This ...

Online social networks contain a wealth of multimodal data with text and images, providing a promising new opportunity for the early detection of depression. Most existing depression detection methods rely on single modality or simply splice different ...

This research introduces a cost-effective, smartphone-powered, computer-vision-based system for Power Wheelchair Intelligent Assistive Driving (PWC IA-Driving). This system enables the safe, hands-free operation of a Power Wheelchair (PWC) with ...

Manchu language, a minority language of China, is of significant historical and research value. An increasing number of Manchu documents are digitized into image format for better preservation and study. Recently, many researchers focused on identifying ...

Deep learning (DL) has demonstrated exceptional success across various domains, including computer vision, natural language processing, and speech recognition. However, the training and inference processes of DL models typically require ...

In an e-commerce platform recommendation system, accurately mining users’ preferences and hidden information has always been an important initiative. In this study, based on the potential preferences and hidden characteristics of users, we ...

Electrocardiograms (ECGs) and phonocardiograms (PCGs) are two modalities to provide complementary diagnostic information for improving the early detection accuracy of cardiovascular diseases (CVDs). Existing multi-modality methods mainly used the ...

As the product of the combination of edge computing and artificial intelligence, edge intelligence (EI) not only solves the problem of insufficient computing capacity of the end device, but also can provide users with various types of intelligent ...

Cone-beam computed tomography (CBCT) is generally reconstructed with hundreds of two-dimensional X-Ray projections through the FDK algorithm, and its excessive ionizing radiation of X-Ray may impair patients’ health. Two common dose-reduction ...

• A novel hybrid strategy for lowering the dose of CBCT.
• A novel JDINet for restoring noise-free and full-view projections.
• A FSSIM loss for preserving delicate structures in projections.
• A complete framework for low-dose CBCT ...

• We propose Fast-Unet based on Unet pruning and optimization to recognize navigation paths between rows of peach, orange and kiwifruit.
• We propose to use ASPP for feature extraction in model down-sampling and Bilinear interpolation for ...

The navigation path recognition has been recognized as one of the most important subtasks of intelligent agricultural equipment in orchard operations. However, there are still some challenges in recognizing navigation paths between rows of fruit ...

Abstract: The difficulty of monitoring flash flood disasters is substantial, and traditional flood monitoring methods are no longer sufficient to meet the demands of flash flood surveillance. This paper proposes the application of satellite imagery ...

This work introduces a pioneering, engineerable approach to 3D visual localization(3DVG). Current challenges for 2D Visual Grounding (2DVG) and 3DVG are summarized: Absence of Depth Information in 2DVG, Memory and Computational Demands of Global Point ...

Most of existing the dehazing methods have high computational complexity and poor dehazing quality. Therefore, a fast haze removal method based on the haze density classification prior is proposed. Haze density is reflected by the difference ...

• VBIGAN-AD is proposed to capture the distribution of background and anomaly.
• Variational inference and adversarial learning are utilized to improve detection performance.
• Composite loss functions is designed to ensure stable ...

Hyperspectral anomaly detection is aimed at detecting targets with significant spectral differences from their surroundings. Recently, deep generative models have been applied to anomaly detections, while the existing generative adversarial ...

Mammogram image is important for breast cancer screening, and typically obtained in a dual-view form, i.e., cranio-caudal (CC) and mediolateral oblique (MLO), to provide complementary information. However, previous methods mostly learn features from the ...

• A novel unpaired learning-based strategy for low-dose CT reconstruction.
• A GAN-...

Low-dose cone-beam computed tomography (CBCT) is reconstructed from hundreds of 2D X-ray projections of low intensity to reduce ionizing radiation to patients, but its imaging quality suffers from noise degradation. A mainstream ...