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MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints
To address this, we integrate a musculoskeletal system with a learnable parametric hand model, MANO, to create a new model, MS-MANO.
Adaptive Multi-layer Contrastive Graph Neural Networks
AMC-GNN generates two graph views by data augmentation and compares different layers' output embeddings of Graph Neural Network encoders to obtain feature representations, which could be used for downstream tasks.
Seismic Inverse Modeling Method based on Generative Adversarial Network
Seismic inverse modeling is a common method in reservoir prediction and it plays a vital role in the exploration and development of oil and gas.
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
In this paper, we propose a new gradient iteration framework, which redefines the relationship between the above three.
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