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RGB-D salient object detection aims to perform the pixel-wise localization of salient objects from both RGB and depth images, whose challenge mainly comes from how to learn complementary features from each modality. Existing works often use ...

• We design a bidirectional feature fusion model to learn discriminative features.
• We propose a dual consistency loss to learn complementary information.
• We achieve the state-of-the-art performance on several datasets.

Gaze estimation aims to predict accurate gaze direction from natural eye images, which is an extreme challenging task due to both random variations in head pose and person-specific biases. Existing works often independently learn features from ...

In previous studies, customized managerial responses have been viewed as an effective tool for sellers to intervene in online consumer opinions. However, formulating a customized response warrants strategic use of language. To explore this ...

• We examine the effect of language style matching between managerial responses and online customer reviews.
• A high level of language style matching between responses and reviews leads to an increase in subsequent consumer ratings.
• ...

This paper presents a novel computer‐aided computational framework to determine the optimum shape parameters in a welding heat source model using a coupled supervised Gaussian process regression (GPR) and genetic algorithm (GA) approach in ...

In haze scenes, light is scattered and absorbed thus affecting the acquisition of information. However, existing image enhancement methods have limited capabilities and it is challenging to truly eliminate haze. As a result, their application to ...

With the rapid development of information technologies, the security of cyberspace has become increasingly serious. Network intrusion detection is a practical scheme to protect network systems from cyber attacks. However, as new vulnerabilities and ...

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• 3D microelectrode configuration was introduced into C4D microfluidics.
• The proposed C4D microfluidic chip effectively improves detection sensitivity.
• The novel C4D microfluidic can quantify soil N, P and K nutrients on site.

Soil macronutrient nutrients (N, P and K) are critical for crop growth and agricultural production. The rapid and quantitative determination of soil nutrient content is of great importance to guide precise fertilization. To address the difficulty ...

Adversarial attacks have been posing significant security concerns to intelligent systems, such as speaker recognition systems (SRSs). Most attacks assume the neural networks in the systems are known beforehand, while black‐box attacks are ...

• Few studies have explored the relationship between social gamification and user fatigue.
• This paper explores the impact of social gamification on users’ psychological stress and fatigue, as well as the moderating effects of player ...

Social gamification design has been widely used in various industries to enhance user engagement. Although social gamification design can help to shape user behavior to some extent, this design mechanism has significant negative effects on users. ...

Video Person Re-Identification (Re-ID) is a task of retrieving persons from multi-camera surveillance systems. Despite the progress made in leveraging spatio-temporal information in videos, occlusion in dense crowds still hinders further progress. To ...

As an emerging consumer electronic product, the use of unmanned aerial vehicle(UAV) for a variety of tasks has received growing attention and favor in the enterprise or individual consumer electronics market in recent years. The deep neural network based ...

Pedestrian trajectory prediction in a first-person view has recently attracted much attention due to its importance in autonomous driving. Recent work utilizes pedestrian character information, i.e., action and appearance, to improve the learned ...

Multi-Object Tracking (MOT) remains a vital component of intelligent video analysis, which aims to locate targets and maintain a consistent identity for each target throughout a video sequence. Existing works usually learn a discriminative feature ...

Weakly-supervised Video Anomaly Detection (W-VAD) aims to detect abnormal events in videos given only video-level labels for training. Recent methods relying on multiple instance learning (MIL) and self-training achieve good performance, but they tend to ...

Unsupervised person re-identification (Re-ID) is challenging due to the lack of ground truth labels. Most existing methods employ iterative clustering to generate pseudo labels for unlabeled training data to guide the learning process. However, how to ...

Smart meter-based individual load forecasts are more and more widely deployed to serve smart grid and home energy management. Customary load forecasting systems collect a massive amount of fine-grained electrical data from people’s smart meters in ...

Unsupervised Person Re-Identification (Re-ID) is challenging due to the lack of ground-truth labels. Most existing methods address this problem by progressively mining high-confidence pseudo labels to guide the feature learning process. However, ...

• We design a novel adversarial contrastive feature learning (ACFL) framework for unsupervised person Re-ID, which can generate hard samples with high-confidence pseudo labels to guide the discriminative feature learning process.
• We ...

Online reviews play a crucial role in comprehending user rating behavior and improving personalized recommendations in e-commerce. However, existing review-based recommendation systems ignore the influence of theory-driven and context ...

• A cognitive process-driven DL recommendation model is proposed by integrating textual review and context information.
• The framework of the proposed model mimics the human brain's cognitive process for predicting user rating behavior.

Medical image segmentation faces current challenges in effectively extracting and fusing long-distance and local semantic information, as well as mitigating or eliminating semantic gaps during the encoding and decoding process. To alleviate the ...

• CFATransUnet uses Transformer and CNN blocks as the backbone network, equipped with CCFT and CCFA modules.
• The CCFT module mitigates semantic asymmetry by cross-level global feature reintegration through self-attention.
• The CCFA ...

The opposition-based differential evolution (ODE) cannot adaptively adjust the number of individuals partake opposition-based learning, which makes it difficult to solve complex optimization problems. In this manuscript, we present an innovative ...