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Found 9 papers, 4 papers with code
MatSAM: Efficient Extraction of Microstructures of Materials via Visual Large Model
Efficient and accurate extraction of microstructures in micrographs of materials is essential in process optimization and the exploration of structure-property relationships.
Spatial-Related Sensors Matters: 3D Human Motion Reconstruction Assisted with Textual Semantics
Leveraging wearable devices for motion reconstruction has emerged as an economical and viable technique.
Dense residual Transformer for image denoising
In this paper, we proposed an image denoising network structure based on Transformer, which is named DenSformer.
Data privacy protection in microscopic image analysis for material data mining
The core contributions are as follows: 1) the federated learning algorithm is introduced into the polycrystalline microstructure image segmentation task to make full use of different user data to carry out machine learning, break the data island and improve the model generalization ability under the condition of ensuring the privacy and security of user data; 2) A data sharing strategy based on style transfer is proposed.
End-to-End Learning for Simultaneously Generating Decision Map and Multi-Focus Image Fusion Result
In this work, to handle the requirements of both output image quality and comprehensive simplicity of structure implementation, we propose a cascade network to simultaneously generate decision map and fused result with an end-to-end training procedure.
SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion
In this work, we propose a novel unsupervised deep learning model to address multi-focus image fusion problem.
WPU-Net: Boundary Learning by Using Weighted Propagation in Convolution Network
In this work, we propose WPU-net that redesigns the architecture and weighted loss of U-Net, which forces the network to integrate information from adjacent slices and pays more attention to the topology in boundary detection task.
Data augmentation in microscopic images for material data mining
Recent progress in material data mining has been driven by high-capacity models trained on large datasets.
Robust and customized methods for real-time hand gesture recognition under object-occlusion
Dynamic hand tracking and gesture recognition is a hard task since there are many joints on the fingers and each joint owns many degrees of freedom.
Human-Computer Interaction
