4,222 Result(s)
within
Chapter
**li Zhang
Image Processing and Computer Vision
Pattern Recognition
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Chapter and Conference Paper
Research on Algorithms of Lateral Face Recognition Based on Data Generation
With the rapid progress of artificial intelligence, the methods of face recognition have also achieved considerable progress. However, when multiple head poses are present, the accuracy of face recognition dec...
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Chapter and Conference Paper
High Capacity Reversible Data Hiding in Encrypted Images Based on Pixel Value Preprocessing and Block Classification
Reversible data hiding in encrypted images (RDHEI) can simultaneously achieve secure transmission of images and secret storage of embedded additional data, which can be used for cloud storage and privacy prote...
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Chapter and Conference Paper
Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost
Industrial process safety has always been a concern for engineers and researchers. Fault diagnosis frameworks based on data-driven methods are prevalent and play a vital role in guaranteeing industrial process...
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Chapter and Conference Paper
Self-supervised Edge Structure Learning for Multi-view Stereo and Parallel Optimization
Recent studies have witnessed that many self-supervised methods obtain clear progress on the multi-view stereo (MVS). However, existing methods ignore the edge structure information of the reconstructed target...
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Chapter and Conference Paper
TNT-Net: Point Cloud Completion by Transformer in Transformer
Estimating the overall structure of a point cloud from a partial 3D point cloud input is a crucial task in computer vision. However, existing point cloud completion methods often overlook object detail informa...
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Chapter and Conference Paper
Isolation and Integration: A Strong Pre-trained Model-Based Paradigm for Class-Incremental Learning
Continual learning aims to effectively learn from streaming data, adapting to emerging new classes without forgetting old ones. Conventional models without pre-training are constructed from the ground up, suff...
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Chapter and Conference Paper
ROSA-Net: Rotation-Robust Structure-Aware Network for Fine-Grained 3D Shape Retrieval
Fine-grained 3D shape retrieval aims to retrieve 3D shapes similar to a query shape in a repository with models belonging to the same class, which requires shape descriptors to represent detailed geometric inf...
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Chapter and Conference Paper
Parameters Efficient Fine-Tuning for Long-Tailed Sequential Recommendation
In an era of information explosion, recommendation systems play an important role in people’s daily life by facilitating content exploration. It is known that user activeness, i.e., number of behaviors, tends to ...
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Chapter and Conference Paper
Self-distillation Enhanced Vertical Wavelet Spatial Attention for Person Re-identification
Person re-identification is a challenging problem in computer vision, aiming to accurately match and recognize the same individual across different viewpoints and cameras. Due to significant variations in appe...
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Chapter and Conference Paper
Structural Health Monitoring of Similar Gantry Crane Based on Federated Learning Algorithm
When using Internet of Things (IoT) technology for health monitoring of similar batches of identical gantry cranes, uploading all their structural data to a cloud server would result in significant bandwidth w...
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Chapter and Conference Paper
GDTNet: A Synergistic Dilated Transformer and CNN by Gate Attention for Abdominal Multi-organ Segmentation
As one of the key problems in computer-aided medical image analysis, learning how to model global relationships and extract local details is crucial to improve the performance of abdominal multi-organ segmenta...
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Chapter and Conference Paper
Denoised Dual-Level Contrastive Network for Weakly-Supervised Temporal Sentence Grounding
The task of temporal sentence grounding aims to localize the target moment corresponding to a given natural language query. Due to the large burden of labeling the temporal boundaries, weakly-supervised method...
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Chapter and Conference Paper
Silhouette-Based 6D Object Pose Estimation
For a long time, deep learning-based 6D object pose estimation networks have lacked the ability to address the problem of pose estimation of the unknown objects beyond the training datasets, due to the closed-...
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Chapter and Conference Paper
Algorithm for Human Abnormal Behavior Recognition Based on Improved Spatial Temporal Graph Convolutional Networks
With the increasing demand for public safety, the field of abnormal human behavior recognition has undergone significant development. In addressing the low accuracy issue of existing abnormal behavior recognit...
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Chapter and Conference Paper
ASF-Conformer: Audio Scoring Conformer with FFC for Speaker Verification in Noisy Environments
Background noise significantly impacts speech intelligibility, reducing the accuracy and reliability of the speaker verification system. Most existing noise reduction algorithms are specific to certain types o...
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Chapter and Conference Paper
A U-Shaped Spatio-Temporal Transformer as Solver for Motion Capture
Motion capture (MoCap) suffers from inevitable noises. The raw markers can be mislabeled, occluded, or contain positional noise, which must be refined before being used for production. However, the clean-up of...
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Chapter and Conference Paper
An Analysis of the Generalized Tit-for-Tat Strategy Within the Framework of Memory-One Strategies
The Tit-for-tat strategy is a traditional strategy in game theory. In the Prisoner’s Dilemma, the TFT strategy has been proven to be strong. However, within a four-component Memory-One strategy framework, the ...
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Chapter and Conference Paper
Zero-Shot Real Facial Attribute Separation and Transfer at Novel Views
Real-time and zero-shot attribute separation of a given real-face image, allowing attribute transfer and rendering at novel views without the aid of multi-view information, has been demonstrated to be benefici...
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Chapter and Conference Paper
Unsupervised Multi-collaborative Learning Network for 3D Face Reconstruction
Monocular image-based 3D fine face reconstruction techniques aim to reconstruct 3D faces with rich face details from a single image. Existing methods have achieved remarkable results, but they cannot accuratel...
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Chapter and Conference Paper
Multi-scale Transformer with Decoder for Image Quality Assessment
Blind image quality assessment (BIQA) is of great significance in image processing field. However, due to diverse image content and complex types of distortions, the issue of BIQA has not been fully resolved. ...
