Yaonan Wang
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View article: Automated Neural Architecture Design for Industrial Defect Detection
Automated Neural Architecture Design for Industrial Defect Detection Open
Industrial surface defect detection (SDD) is critical for ensuring product quality and manufacturing reliability. Due to the diverse shapes and sizes of surface defects, SDD faces two main challenges: intraclass difference and interclass s…
Resilient Multimodal Industrial Surface Defect Detection With Uncertain Sensors Availability Open
Multimodal industrial surface defect detection (MISDD) aims to identify and locate defect in industrial products by fusing RGB and 3D modalities. This article focuses on modality-missing problems caused by uncertain sensors availability in…
SAMIR, an efficient registration framework via robust feature learning from SAM Open
Image registration is a fundamental task in medical image analysis. Deformations are often closely related to the morphological characteristics of tissues, making accurate feature extraction crucial. Recent weakly supervised methods improv…
Embodied Intelligence for Micro‐Integrated Energy Systems: Key Technologies and Applications Open
Micro‐integrated energy systems, as a small‐scale, distributed energy supply system that integrates multiple energy technologies, is one of the most promising application directions for artificial intelligence. Similar to robots, micro‐int…
You Can Only Tune Normalization: A Simple and Effective Approach to Parameter-Efficient Fine-Tuning Open
To tackle the issue of excessive parameter volumes during fine-tuning of large-scale pre-trained models with full parameters, Parameter-Efficient Fine-Tuning (PEFT) methods have been introduced. The core concept involves freezing the backb…
ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Open
Jointly addressing Byzantine attacks and privacy leakage in distributed machine learning (DML) has become an important issue. A common strategy involves integrating Byzantine-resilient aggregation rules with differential privacy mechanisms…
View article: Unsupervised Deformable Image Registration with Structural Nonparametric Smoothing
Unsupervised Deformable Image Registration with Structural Nonparametric Smoothing Open
Learning-based deformable image registration (DIR) accelerates alignment by amortizing traditional optimization via neural networks. Label supervision further enhances accuracy, enabling efficient and precise nonlinear alignment of unseen …
Quantum machine learning for multiclass classification beyond kernel methods Open
Quantum machine learning is considered one of the current research fields with immense potential. In recent years, Havlíček et al. [Nature 567, 209-212 (2019)] have proposed a quantum machine learning algorithm with quantum-enhanced featur…
Reconsider the Template Mesh in Deep Learning-based Mesh Reconstruction Open
Mesh reconstruction is a cornerstone process across various applications, including in-silico trials, digital twins, surgical planning, and navigation. Recent advancements in deep learning have notably enhanced mesh reconstruction speeds. …
View article: Foundation models and intelligent decision-making: Progress, challenges, and perspectives
Foundation models and intelligent decision-making: Progress, challenges, and perspectives Open
Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and ad…
View article: Semantic Ambiguity Modeling and Propagation for Fine-Grained Visual Cross View Geo-Localization
Semantic Ambiguity Modeling and Propagation for Fine-Grained Visual Cross View Geo-Localization Open
Visual cross view geo-localization is generally approached within a joint retrieval-and-calibration framework. However, existing methods overlook semantic ambiguities arising from query and reference images characterized by low overlap, dy…
Key Technologies for Machine Vision for Picking Robots: Review and Benchmarking Open
The increase in precision agriculture has promoted the development of picking robot technology, and the visual recognition system at its core is crucial for improving the level of agricultural automation. This paper reviews the progress of…
FAMHE-Net: Multi-Scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection Open
Object detection in remote sensing images is essential for applications like unmanned aerial vehicle (UAV)-assisted agricultural surveys and aerial traffic analysis, facing unique challenges such as low resolution, complex backgrounds, and…
Deep Stereo Network With Cross-Correlation Volume Construction and Least Square Aggregation Open
Stereo matching is of great importance in robot operation, autonomous driving and virtual reality. Large textureless regions and depth discontinuity regions are still the error-prone regions of stereo matching tasks. Traditional correlatio…
View article: AC-YOLO: citrus detection in the natural environment of orchards
AC-YOLO: citrus detection in the natural environment of orchards Open
In the natural environment, the shape and color of fruits can vary greatly due to various factors, and the growth of fruits is irregular, shaded by leaves and branches, and there are phenomena such as overlapping fruits. The complex backgr…
Tacit Learning with Adaptive Information Selection for Cooperative Multi-Agent Reinforcement Learning Open
In multi-agent reinforcement learning (MARL), the centralized training with decentralized execution (CTDE) framework has gained widespread adoption due to its strong performance. However, the further development of CTDE faces two key chall…
From Global to Local: A Dual-Branch Structural Feature Extraction Method for Hyperspectral Image Classification Open
Extracting discriminative spectral-spatial features from hyperspectral images (HSIs) remains a crucial topic within the remote sensing community. However, most feature extraction methods suffer from coarse textures, leading to poor perform…
FAMHE-Net: Multi-scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection Open
Object detection in remote sensing images is essential for applications like UAV-assisted agricultural surveys and aerial traffic analysis, facing unique challenges such as low resolution, complex backgrounds, and variability of object sca…
View article: EADReg: Probabilistic Correspondence Generation with Efficient Autoregressive Diffusion Model for Outdoor Point Cloud Registration
EADReg: Probabilistic Correspondence Generation with Efficient Autoregressive Diffusion Model for Outdoor Point Cloud Registration Open
Diffusion models have shown the great potential in the point cloud registration (PCR) task, especially for enhancing the robustness to challenging cases. However, existing diffusion-based PCR methods primarily focus on instance-level scena…