Titlebook: Intelligent Robotics and Applications; 16th International C Huayong Yang,Honghai Liu,Zhiyong Wang Conference proceedings 2023 The Editor(s)

Pedagogy

Large-Parallax Multi-camera Calibration Method for Indoor Wide-Baseline Scenese multi-camera system by computing the optimal vanishing point through the extraction of orthogonal parallel lines within each camera’s view. This approach begins by extracting orthogonal parallel lines from the image to establish an accurate indoor 3D model. Furthermore, we incorporate the easily o

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All-in-One Image Dehazing Based on Attention Mechanisme attention mechanism, we use summation operations between the feature layer obtained after each attention operation and the input layer. Our model prioritizes attention to the dense haze region while maintaining overall brightness. Extensive experiments demonstrate that our method surpasses state-o

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良心

FairShare: An Incentive-Based Fairness-Aware Data Sharing Framework for Federated Learning reliable outcomes. Experiments confirm the VCG-based mechanism’s truthfulness and Shapley Value’s fairness in payment allocation. In conclusion, FairShare addresses fairness challenges and fosters reliability in federated learning, facilitating dependable human-machine interactions. Implementing Fa

闲荡

Combating Label Ambiguity with Smooth Learning for Facial Expression Recognitioniscriminative features. The estimated weights adapt to the sparse representation of central loss to selectively achieve intra-class compactness and inter-class separation of relevant information in the embedding space. The proposed ACD approach is superior compared to state-of-the-art

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EMG Denoising Based on CEEMDAN-PE-WT Algorithmthreshold denoising is applied. Results show that EMG signals denoised by the proposed CEEMDAN-PE-WT algorithm perform a higher signal-to-noise ratio (SNR) and lower root mean square error (RMSE) compared with WT, EMD and CEEMDAN denoising methods.

提升

AS-TransUnet: Combining ASPP and Transformer for Semantic Segmentationid module can obtain more receptive fields to obtain multi-scale information. In addition, we add an attention module to the decoder to help the model learn relevant features. To verify the performance and efficiency of the model, we conducted experiments on two common data sets and compared them wi

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The Application of Hybrid Dynamic Recurrent Fuzzy Neural Network in Lower Limb Rehabilitation Functier then proposes a hybrid optimization learning method for the above network, which includes particle swarm optimization (PSO) and recursive least squares estimator (RLSE). PSO modifies the function parameters used to calculate the membership degree to optimize the fitness of fuzzy rules. However, t

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