Kuangrong Hao
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View article: A Robust 3D Fixed-Area Quality Inspection Framework for Production Lines
A Robust 3D Fixed-Area Quality Inspection Framework for Production Lines Open
Introducing deep learning methods into the quality inspection of production lines can reduce labor and improve efficiency, with great potential for the development of manufacturing systems. However, in specific closed production-line envir…
View article: CRISPR/xCas9-mediated corazonin knockout reveals the effectiveness of xCas9 editing and the crucial role of corazonin in insect cuticle development
CRISPR/xCas9-mediated corazonin knockout reveals the effectiveness of xCas9 editing and the crucial role of corazonin in insect cuticle development Open
View article: Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients
Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients Open
Federated learning (FL) enables collaborative training of deep learning models without requiring data to leave local clients, thereby preserving client privacy. The aggregation process on the server plays a critical role in the performance…
View article: Multi-Target Federated Backdoor Attack Based on Feature Aggregation
Multi-Target Federated Backdoor Attack Based on Feature Aggregation Open
Current federated backdoor attacks focus on collaboratively training backdoor triggers, where multiple compromised clients train their local trigger patches and then merge them into a global trigger during the inference phase. However, the…
View article: Micro-KTNet: Microstructure knowledge transfer learning for fiber masterbatch agglomeration recognition
Micro-KTNet: Microstructure knowledge transfer learning for fiber masterbatch agglomeration recognition Open
Fiber masterbatch production suffers from inherent agglomeration effect of high-concentration color masterbatches, negatively impacting color uniformity, particle dispersion, and thermal stability in fiber masterbatch, and ultimately the q…
View article: Multi-Target Federated Backdoor Attack Based on Feature Aggregation
Multi-Target Federated Backdoor Attack Based on Feature Aggregation Open
View article: An Agglomeration Detection Framework In High-Performance Fiber Cross-scale Ultrastructure
An Agglomeration Detection Framework In High-Performance Fiber Cross-scale Ultrastructure Open
View article: Biomem-Gcn: A Biologically Inspired Memory-Enhanced Graph Convolutional Network for Interpretable Data-Driven Modeling of Complex Industrial Processes
Biomem-Gcn: A Biologically Inspired Memory-Enhanced Graph Convolutional Network for Interpretable Data-Driven Modeling of Complex Industrial Processes Open
View article: BanditCAT and AutoIRT: Machine Learning Approaches to Computerized Adaptive Testing and Item Calibration
BanditCAT and AutoIRT: Machine Learning Approaches to Computerized Adaptive Testing and Item Calibration Open
In this paper, we present a complete framework for quickly calibrating and administering a robust large-scale computerized adaptive test (CAT) with a small number of responses. Calibration - learning item parameters in a test - is done usi…
View article: Adaptive normal vector guided evolutionary multi- and many-objective optimization
Adaptive normal vector guided evolutionary multi- and many-objective optimization Open
Most existing multi-objective evolutionary algorithms relying on fixed reference vectors originating from an ideal or a nadir point may fail to perform well on multi- and many-objective optimization problems with various convexity or shape…
View article: A Hypothetical Defenses-Based Training Framework for Generating Transferable Adversarial Examples
A Hypothetical Defenses-Based Training Framework for Generating Transferable Adversarial Examples Open
View article: An Edge-Specific Message Graph Convolution Network Based on Community Graph Structure Generation for Polymerization Process Prediction
An Edge-Specific Message Graph Convolution Network Based on Community Graph Structure Generation for Polymerization Process Prediction Open
View article: From Visual Features to Key Concepts: A Dynamic and Static Concept-Driven Approach for Video Captioning
From Visual Features to Key Concepts: A Dynamic and Static Concept-Driven Approach for Video Captioning Open
View article: Grid Mamba: Grid State Space Model for Large-Scale Point Cloud Analysis
Grid Mamba: Grid State Space Model for Large-Scale Point Cloud Analysis Open
View article: Enhancing Large Language Models by Fuzzy Theory for Commonsense Reasoning
Enhancing Large Language Models by Fuzzy Theory for Commonsense Reasoning Open
View article: Multi-level deep domain adaptive adversarial model based on tensor-train decomposition for industrial time series forecasting
Multi-level deep domain adaptive adversarial model based on tensor-train decomposition for industrial time series forecasting Open
The polyester industry is a complex process industry, building a time series prediction model for new production lines or equipment with new sensors can be challenging due to a lack of historical data. The time-series data collected from s…
View article: A robot-assisted adaptive communication recovery method in disaster scenarios
A robot-assisted adaptive communication recovery method in disaster scenarios Open
Communication recovery is necessary for rescue and reconstruction scenarios including earthquakes, typhoons, floods, etc. The rapid and stable communication link can provide efficient victims’ real-time information for the rescue process. …
View article: Semantic Hybrid Signal Temporal Logic Learning-Based Data-Driven Anomaly Detection in the Textile Process
Semantic Hybrid Signal Temporal Logic Learning-Based Data-Driven Anomaly Detection in the Textile Process Open
The development of sensor networks allows for easier time series data acquisition in industrial production. Due to the redundancy and rapidity of industrial time series data, accurate anomaly detection is a complex and important problem fo…
View article: A spatial–spectral adaptive learning model for textile defect images recognition with few labeled data
A spatial–spectral adaptive learning model for textile defect images recognition with few labeled data Open
Textile defect recognition is a significant technique in the production processes of the textile industry. However, in the practical processes, it is hard to acquire large amounts of textile defect samples. Meanwhile, the textile samples w…
View article: A Moth–Flame Optimized Echo State Network and Triplet Feature Extractor for Epilepsy Electro-Encephalography Signals
A Moth–Flame Optimized Echo State Network and Triplet Feature Extractor for Epilepsy Electro-Encephalography Signals Open
The analysis of epilepsy electro-encephalography (EEG) signals is of great significance for the diagnosis of epilepsy, which is one of the common neurological diseases of all age groups. With the developments of machine learning, many data…
View article: MS-FTSCNN: An EEG Emotion Recognition Method from the Combination of Multi-Domain Features
MS-FTSCNN: An EEG Emotion Recognition Method from the Combination of Multi-Domain Features Open
View article: Multi-Objective Evolutionary for Object Detection Mobile Architectures Search
Multi-Objective Evolutionary for Object Detection Mobile Architectures Search Open
Recently, Neural architecture search has achieved great success on classification tasks for mobile devices. The backbone network for object detection is usually obtained on the image classification task. However, the architecture which is …
View article: Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification
Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification Open
To address the trade-off problem of quality-diversity for the generated images in imbalanced classification tasks, we research on over-sampling based methods at the feature level instead of the data level and focus on searching the latent …
View article: Vision Transformer with Convolutions Architecture Search
Vision Transformer with Convolutions Architecture Search Open
Transformers exhibit great advantages in handling computer vision tasks. They model image classification tasks by utilizing a multi-head attention mechanism to process a series of patches consisting of split images. However, for complex ta…
View article: Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects
Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects Open
Visual sensation and perception refers to the process of sensing, organizing, identifying, and interpreting visual information in environmental awareness and understanding. Computational models inspired by visual perception have the charac…
View article: Dynamic immune cooperative scheduling of agricultural machineries
Dynamic immune cooperative scheduling of agricultural machineries Open
Considering the low flexibility and efficiency of the scheduling problem, an improved multi-objective immune algorithm with non-dominated neighbor-based selection and Tabu search (NNITSA) is proposed. A novel Tabu search algorithm (TSA)-ba…
View article: Enhanced Gradient for Differentiable Architecture Search
Enhanced Gradient for Differentiable Architecture Search Open
In recent years, neural architecture search (NAS) methods have been proposed for the automatic generation of task-oriented network architecture in image classification. However, the architectures obtained by existing NAS approaches are opt…
View article: MLMA-Net: multi-level multi-attentional learning for multi-label object detection in textile defect images
MLMA-Net: multi-level multi-attentional learning for multi-label object detection in textile defect images Open
For the sake of recognizing and classifying textile defects, deep learning-based methods have been proposed and achieved remarkable success in single-label textile images. However, detecting multi-label defects in a textile image remains c…
View article: Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification
Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification Open
Relation classification (RC) task is one of fundamental tasks of information extraction, aiming to detect the relation information between entity pairs in unstructured natural language text and generate structured data in the form of entit…
View article: Optimizing Deep Neural Networks through Neuroevolution with Stochastic Gradient Descent
Optimizing Deep Neural Networks through Neuroevolution with Stochastic Gradient Descent Open
Deep neural networks (DNNs) have achieved remarkable success in computer vision; however, training DNNs for satisfactory performance remains challenging and suffers from sensitivity to empirical selections of an optimization algorithm for …