815 Result(s)
within
Computer Science
Computer Communication Networks
Pattern Recognition
**u-**u Zhang
Chapter
Conference Paper
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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
LEAD: LiDAR Extender for Autonomous Driving
3D perception using sensors under vehicle industrial standards is the rigid demand in autonomous driving. MEMS LiDAR emerges with irresistible trend due to its lower cost, more robust, and meeting the mass-pro...
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Chapter and Conference Paper
Sequential Style Consistency Learning for Domain-Generalizable Text Recognition
As a task aiming to recognize text from images, text recognition is of great significance in both industry and academia. The vast majority of existing text recognition methods use text images with the same sty...
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Chapter and Conference Paper
Weakly-Supervised Grounding for VQA with Dual Visual-Linguistic Interaction
Visual question answer (VQA) grounding, aimed at locating the visual evidence associated with the answers while answering questions, has attracted increasing research interest. To locate the evidence, most exi...
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Chapter and Conference Paper
RsMmFormer: Multimodal Transformer Using Multiscale Self-attention for Remote Sensing Image Classification
Remote Sensing (RS) has been widely utilized in various Earth Observation (EO) missions, including land cover classification and environmental monitoring. Unlike computer vision tasks on natural images, collec...
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Chapter and Conference Paper
Concealed Object Segmentation with Hierarchical Coherence Modeling
Concealed object segmentation (COS) is a challenging task that involves localizing and segmenting those concealed objects that are visually blended with their surrounding environments. Despite achieving remark...
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Chapter and Conference Paper
Structural Recognition of Handwritten Chinese Characters Using a Modified Part Capsule Auto-encoder
Handwritten Chinese character recognition has achieved high accuracy using deep neural networks (DNNs), but the structural recognition (which offers structural interpretation, e.g., stroke and radical composit...
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Chapter and Conference Paper
Multi-trends Enhanced Dynamic Micro-video Recommendation
The explosively generated micro-videos on content sharing platforms call for recommender systems to permit personalized micro-video discovery with ease. Recent advances in micro-video recommendation have achie...
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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. ...
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Chapter and Conference Paper
EFPNet: Effective Fusion Pyramid Network for Tiny Person Detection in UAV Images
Unmanned Aerial Vehicles (UAVs) have found extensive applications in the field of rescue and navigation scenarios. The objects in UAV images are generally with small sizes, which rises a serious challenge of o...
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Chapter and Conference Paper
SPCTNet: A Series-Parallel CNN and Transformer Network for 3D Medical Image Segmentation
Medical image segmentation is crucial for lesion localization and surgical navigation. Recent advancements in medical image segmentation have been driven by Convolutional Neural Networks (CNNs) and Transformer...
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Chapter and Conference Paper
Robust Self-contact Detection Based on Keypoint Condition and ControlNet-Based Augmentation
Existing self-contact detection methods have difficulty detecting dense per-vertex self-contact. Dataset collection for existing self-contact detection methods is costly and inefficient, as it requires differe...
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Chapter and Conference Paper
End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation
With the development of deep learning, more and more related techniques are used in recommender system, making it more effective and reliable. However, due to the various distribution of real-time data, those ...
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Chapter and Conference Paper
Diagnosis Then Aggregation: An Adaptive Ensemble Strategy for Keyphrase Extraction
Keyphrase extraction (KE) is a fundamental task in the information extraction, which has recently gained increasing attention. However, when facing text with complex structure or high noise, current individual...
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Chapter and Conference Paper
LANet: A Single Stage Lane Detector with Lightweight Attention
Currently, lane detection is one of the key tasks in autonomous driving. Numerous lane detection methods have achieved high accuracy. However, there is still ample room for improvement in develo** techniques...
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Chapter and Conference Paper
A Hybrid Approach for Segmenting Non-ideal Iris Images Using CGAN and Geometry Constraints
The prevalence of personal mobile devices makes iris authentication being more and more popular. Accurate iris segmentation is critical for authentication. However, it is very challenging, due to iris images c...
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Chapter and Conference Paper
Towards Interpreting Computer Vision Based on Transformation Invariant Optimization
Interpreting how deep neural networks (DNNs) make predictions is a vital field in artificial intelligence, which hinders wide applications of DNNs. Visualization of learned representations helps we humans unde...
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Chapter and Conference Paper
NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges
NICO challenge of out-of-distribution (OOD) generalization for image recognition features two tracks: common context generalization and hybrid context generalization, based on a newly proposed OOD dataset call...
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Chapter and Conference Paper
Decoupled Mixup for Out-of-Distribution Visual Recognition
Convolutional neural networks (CNN) have demonstrated remarkable performance, when the training and testing data are from the same distribution. However, such trained CNN models often largely degrade on testin...
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Chapter and Conference Paper
Multi-Task Learning Framework for Emotion Recognition In-the-Wild
This paper presents our system for the Multi-Task Learning (MTL) Challenge in the 4th Affective Behavior Analysis in-the-wild (ABAW) competition. We explore the research problems of this challenge from three a...
