341 Result(s)
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Artificial Intelligence
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Article
CMT-6D: a lightweight iterative 6DoF pose estimation network based on cross-modal Transformer
6DoF pose estimation has received much attention in recent years. A key challenge is the difficulty of estimating object pose when the target texture is weak. In this work, we present the cross-modal Transform...
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Article
Self-Preloading Flexible Attachment Actuator with Multi-Mechanism Hierarchical Structure
Flexible attachment actuators are popular in a wide range of applications, owing to their flexibility and highly reliable attachment. However, their reversible adhesion performance depends on the actual effect...
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Article
Open-Vocabulary Text-Driven Human Image Generation
Generating human images from open-vocabulary text descriptions is an exciting but challenging task. Previous methods (i.e., Text2Human) face two challenging problems: (1) they cannot well handle the open-vocab...
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Article
Few-shot classification with intra-class co-salient learning and holistic metric
Few-shot learning is to learn to discriminate novel classes from a minimal amount of support images. The core of the matter lies in obtaining effective feature representations from limited samples and measurin...
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Article
Orthogonal integral transform for 3D shape recognition with few examples
3D shape recognition with few examples is crucial for applications involving 3D scenes, but typical methods based on surface and view suffer the failure to describe the interior and exterior features uniformly...
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Article
Dual-stream framework for image-based heart infarction detection using convolutional neural networks
Heart infarction has become one of the major causes of global death in recent decades. As the aging society intensifies, many elderly people living alone are facing life-threatening situations brought on by su...
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Article
An improved CapsNet based on data augmentation for driver vigilance estimation with forehead single-channel EEG
Various studies have shown that it is necessary to estimate the drivers’ vigilance to reduce the occurrence of traffic accidents. Most existing EEG-based vigilance estimation studies have been performed on int...
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Article
Ordinal information based facial expression intensity estimation for emotional interaction: a novel semi-supervised deep learning approach
Emotional understanding and expression plays a critical role in social interaction. To analyze children’s emotional interaction automatically, this study focuses on develo** a novel network architecture and ...
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Article
Cluster weighted model based on TSNE algorithm for high-dimensional data
Cluster-weighted models (CWMs) are an important class of machine learning models that are commonly used for modelling complex datasets. However, they are known to suffer from reduced computing efficiency and e...
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Article
A noise-immune and attention-based multi-modal framework for short-term traffic flow forecasting
Accurately forecasting short-term traffic flow is essential for intelligent transportation systems. However, current methods often struggle to fully exploit implicit variation patterns and heterogeneous correl...
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Article
Resolution-sensitive self-supervised monocular absolute depth estimation
Depth estimation is an essential component of computer vision applications for environment perception, 3D reconstruction and scene understanding. Among the available methods, self-supervised monocular depth es...
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Article
Open AccessRII-GAN: Multi-scaled Aligning-Based Reversed Image Interaction Network for Text-to-Image Synthesis
The text-to-image (T2I) model based on a single-stage generative adversarial network (GAN) has significantly succeeded in recent years. However, the generation model based on GAN has two disadvantages: the gen...
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Article
Open AccessGated Fusion Adaptive Graph Neural Network for Urban Road Traffic Flow Prediction
Accurate prediction of traffic flow plays an important role in maintaining traffic order and traffic safety, which is a key task in the application of intelligent transportation systems (ITS). However, the urb...
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Chapter and Conference Paper
Sharding Technologies in Blockchain: Basics, State of the Art, and Challenges
Sharding is one of the key technologies of blockchain scalable characteristics widely used in cryptocurrencies, Internet of Things, supply chain management and other fields. It can achieve high performance sca...
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Chapter and Conference Paper
Auto-Learning-GCN: An Ingenious Framework for Skeleton-Based Action Recognition
The Graph Convolutional Network (GCN) has garnered substantial interest over an extended period owing to its notable efficacy in addressing topological correlations, with particular achievements observed in sk...
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Chapter and Conference Paper
Sketchformer++: A Hierarchical Transformer Architecture for Vector Sketch Representation
With the rising ubiquity of digital touch devices and sketch-based interfaces, freehand sketching has become an essential mode of visual communication. Nevertheless, interpreting these often ambiguous and spar...
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Chapter and Conference Paper
Application of Autoencoder for Control Valve Predictive Analytics
In this paper, we investigated the application of an autoencoder neural network for predictive analytics of control valves, which are crucial components in industrial processes with significant consequences in...
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Article
LRB-T: local reasoning back-projection transformer for the removal of bad weather effects in images
In computer vision, transformers have shown increasing effectiveness for high-level vision tasks. To further cope with low-level vision tasks, we propose a general framework, namely local reasoning back-projec...
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Chapter and Conference Paper
A Unified Framework of Multi-stage Multi-winner Voting: An Axiomatic Exploration
Multi-winner voting plays a crucial role in selecting representative committees based on voter preferences. Previous research has predominantly focused on single-stage voting rules, which are susceptible to ma...
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Chapter and Conference Paper
Preference Contrastive Learning for Personalized Recommendation
Recommender systems play a crucial role in providing personalized services but face significant challenges from data sparsity and long-tail bias. Researchers have sought to address these issues using self-supe...
