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第三十九届中国控制会议

作者： Abdul Rehman Zhen-Tao Liu Dan-Yun Li Bao-Han Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Speech emotion recognition helps enrich next-generation AI with emotional intelligence abilities by grasping the emotion from voice and words. At the current stage, speech emotion recognition（SER） is only used within experimental *** current challenge facing the SER research is the lack of robustness across cultures, languages and even minor differences such as age-gaps of speakers. To create a more adaptable SER in adversarial circumstances, we propose hybrid neural networks architecture that creates a holistic model by embedding the Mel Frequency Cepstrum Coefficients as one-hot inputs such that differences in coefficients in each emotional category are inflated according to their importance. We performed experiments on three different databases to test the cross-corpus effectiveness of the proposed model.

关键词： Emotion Recognition Speech Neural Networks Embedding Cross-corpus

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Spectral Reflectance Reconstruction from Camera Responses by Adaptively Constructing Weight Matrix Combining Colorimetric and Lightness Similarities

Spectral Reflectance Reconstruction from Camera Responses by...

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第三十九届中国控制会议

作者： Xin Wang Hui Jiang Jing-Jing Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

An improved method for spectral reflectance reconstruction from digital camera raw RGB responses of pixels is proposed by adaptively weighting training samples considering colorimetric and lightness similarities. The proposed method was based on an adaptive local weighted linear regression model by using a Gaussian function in weighting matrix *** novelty of our method is designing the weighting matrix combining colorimetric and lightness similarities. The proposed method was tested using two different standard color charts, with a simulated digital camera based on the camera spectral sensitivity. Experimental results indicate that the proposed method exhibits considerable improvements in terms of the spectral reflectance and the colorimetric values in comparison with existing methods.

关键词： Spectral Reflectance Reconstruction Lightness Similarity Pseudo Inverse

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Analysis of Bit-Rock Interaction Models Using Finite Element Simulation Data

Analysis of Bit-Rock Interaction Models Using Finite Element...

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第三十九届中国控制会议

作者： Hengyu Huang Min Wu Sike Ma Luefeng Chen Chengda Lu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The study of bit-rock interaction model is essential to describe the rock breaking process. In practice, it is difficult to get downhole measurement, and the downhole rock-breaking data is difficult to obtain. Therefore, this paper uses finite element simulation to obtain the kinetic data of bit-rock interaction, based on the analysis and comparison of existing models, an effective analysis method is provided for bit-rock interaction. Firstly, by using the Drucker-Prager rock criterion, actual bit and rock parameters, we develop the finite element bit-rock interaction experiments, and we obtain the data of rotating speed, rate-ofpenetration, weight-on-bit. Then, based on multiple nonlinear regression method, we identify the existing Young model, Jorden and Shirley model, Richard model, Ritto model parameters. Through the analysis and comparison of identification effects and characteristics of each model, we obtain the relationship among parameters of the bit-rock interaction.

关键词： Bit-rock interaction Weight on bit Finite element method Parameter identification

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A Composite Cost-Sensitive Neural Network for Imbalanced Classification

A Composite Cost-Sensitive Neural Network for Imbalanced Cla...

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第三十九届中国控制会议

作者： Lei Chen Yuan Zhu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Imbalanced data with skewed class distributions and different misclassification costs is common in many real-world applications. Traditional classification approach does not work well for imbalanced data, because they assume equal costs for each class. To deal with this problem, cost-sensitive approaches assign different misclassification costs for different classes without disrupting the true original distributions of samples. However, due to lack of prior knowledge, the misclassification costs are usually unknown and hard to choose in practice. Whats more, even instances in the same class may have different misclassification costs. As an extension of class-dependent costs, this paper presents a composite cost-sensitive deep neural network(CCS-DNN) for imbalanced classification. A specifically-designed cost-sensitive matrix, which is composed of exampledependent costs and class-dependent costs, is embedded into the loss function to improve the classification performance. And the parameters of both the cost-sensitive matrix and the network are jointly optimized during training. The results of comparative experiments on some benchmark datasets indicate that the CCS-DNN performs better than other baseline methods.

关键词： Cost-sensitive Learning Composite Costs Imbalanced Classification Deep Learning

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A Novel Eye State Detection Method via WBCNN

A Novel Eye State Detection Method via WBCNN

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第三十九届中国控制会议

作者： Zhen-Tao Liu Si-Han Li Cheng-Shan Jiang Dan-Yun Li Man Hao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the field of face recognition and analysis, eye state detection is an essential step, which is the prerequisite and breakthrough of drowsiness estimation and auxiliary driving. This paper presents an eye state detection method based on Weight Binarization Convolution Neural Network（WBCNN）. The weight of the network is constrained by binarization, which can limit the weight to 1 or-1, reducing the power dissipation and internal storage considerably. The human eye state features which can be extracted by convolution neural network effectively, and binary network not only contributes to reducing the storage size of the model, but also accelerates the computation. Experiments on eye state detection were conducted on the Closed Eyes in the wild（CEW） and FER2013 Databases, from which the results show that our method achieved average test accuracy of 97.41%on CEW. We used the FER2013 facial expression database for pre-training, which can make up for the lack of CEW training samples. The computational speed of non-binary is slower than binary network. Moreover, less storage capacity is required by our method.

关键词： Eye state detection Convolution neural network Image processing Weight Binarization

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An Improved Faster-RCNN Algorithm for Object Detection in Remote Sensing Images

An Improved Faster-RCNN Algorithm for Object Detection in Re...

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第三十九届中国控制会议

作者： Rui Liu Zhihua Yu Daili Mo Yunfei Cai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Compared with conventional object detection, remote sensing images are taken from the air. The angle of view is not fixed and the object direction, scale which compared with conventional object detection algorithm are quite different. These factors lead to the object detection in remote sensing images difficult. To solve the above problems, this paper proposes an improved remote sensing object detection method based on Faster-RCNN algorithm. Using online difficult example mining technology,feature pyramid structure, Soft-NMS technology, and RoI-Align technology to enhance the capabilities of Faster-RCNN in small object detection task in remote sensing images. The algorithm in this paper was evaluated on the RSOD-Dataset, compared with the original Faster-RCNN algorithm, the proposed algorithm improves the detection accuracy and training convergence speed,which shows that these improvements are of great significance to the object detection algorithm of remote sensing images.

关键词： Remote Sensing Images Faster-RCNN Small Object Detection

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Delay-Dependent Stability Analysis of Delayed Discrete-Time systems via State-Connecting-Based Zero-Value Equations

Delay-Dependent Stability Analysis of Delayed Discrete-Time ...

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第三十九届中国控制会议

作者： Ke-You Xie Wen-Hu Chen Li Jin Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper is concerned with the stability analysis of discrete time-delay system. Firstly, an improved augmented functional form is proposed and the positive definite condition of functional is derived. Then, the forward difference of functional is estimated by applying summation inequalities and a state-connecting-based zero-value equation. As a result, an improved stability criterion is established. Finally, a numerical example is given to show the efficiency and merit of the proposed method.

关键词： Discrete-time systems stability analysis time-varying delay zero-value equation

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Stability Analysis of Milling Process With Time-Varying Delays Via Lyapunov-Krasovskii Functional

Stability Analysis of Milling Process With Time-Varying Dela...

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第三十九届中国控制会议

作者： Jiang He Chen Yan Hong-Zhang Wang Dan-Yun Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The regenerative chatter during milling seriously affects the stability of the *** paper proposes a method based on Lyapunov-Krasovski functional analysis for the stability of the milling ***,the mechanism analysis of the milling process is performed,then the state-space equation of the time-varying delay system caused by the regeneration effect is ***,based on the model of a time-delay system,a stability criterion is developed by constructing an augmented LyapunovKrasovski functional(LKF) and using auxiliary function inequality with reciprocally convex combination ***,the validity of the method is verified through an example,and the milling stability domain lobe diagram with a parameter combination of spindle speed-cutting depth is obtained which provides operational guidelines to guarantee a stable vibration-free process.

关键词： Milling process time-varying delay Lyapunov reciprocally combination technology stability

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Motion Semantic Enhancement and Autonomous Information Mining for Static-Dynamic Visual Emotion Recognition in Human–Robot Interaction

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Cheng-Shan Jiang Zhen-Tao Liu Edwardo F. Fukushima Jinhua She School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Ministry of Education and Engineering Research Center of Intelligent Technology for Geo-Exploration China University of Geosciences Wuhan China School of Engineering Tokyo University of Technology Hachioji Japan

The advancement of static-dynamic visual emotion recognition (DVER) plays a pivotal role in the evolution of intelligent and empathetic machines. Currently, the progress of static visual emotion recognition (SVER) faces challenges, primarily the need to balance model efficiency with robust recognition performance. Moreover, obstacles such as noisy data and limited labeled datasets restrict models from effectively learning the appearance features and dynamic dependencies intrinsic to DVER. In the realm of SVER, facial pixel, and semantic representation are derived using a lightweight surface and landmark features embedding network, followed by neuron-energy-based feature fusion-filtering to enhance the fusion of semantic representations positively. For DVER, a Global Anchor-Dependent Noisy Emotional Data Filtering (GADNEF) method is employed for noisy label learning (NLL), facilitating clip-wise filtering of ambiguous data via iterative computations of frame-wise attention statistics across batches. Furthermore, a self-supervised learning (SSL) paradigm based on a unified appearance and motion-guided masked autoencoder (UAMGMAE) is implemented, enabling large-scale knowledge transfer tailored for video-based facial expression analysis. Our approach has achieved accuracies of 97.07%, 98.90%, 61.39%, and 92.28% on SVER datasets including KDEF, RaFD, SFEW, and RAF-DB, respectively, while the weighted average recall (WAR) and unweighted average recall (UAR) on DVER datasets such as DFEW and MAFW were 75.12%, 64.37%, 55.26%, and 42.53%, respectively. A preliminary application experiment has also been conducted to validate the practical applicability of our method within human–robot interaction (HRI) scenarios.

关键词： Noise measurement Visualization Emotion recognition Semantics Human-robot interaction Filtering Feature extraction Training Neurons Transformers

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Improved-YOLOv3 network for object detection in simulated Space Solar Power systems images

Improved-YOLOv3 network for object detection in simulated Sp...

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第三十九届中国控制会议

作者： Guangjun Wang Nongwei Lei Huimin Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, the object detection technology based on deep learning is applied to the assembly process of space power station simulation, which can provide assistance for the attitude adjustment and navigation of the aircraft through the detection of some components. Firstly, the 3 D modeling and rendering of the space power station are carried out, on which the image dataset is collected and established. Then, based on the YOLOv3 network, we improve the structure of feature *** fusing the information of shallow and deep features, we can improve the detection ability of the network for different scale *** and quantitative experimental results show that the improved YOLOv3 network can accurately and effectively detect the key components of the Space solar power station.

关键词： Space Solar Power systems object detection YOLOv3 multiscale features

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