Search Results for author:
Found 10 papers, 3 papers with code
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE
Owing to the combination of the unified architecture and pre-training task, EVE is easy to scale up, enabling better downstream performance with fewer resources and faster training speed.
DCEM-PINNs: A deep complementary energy method for solid mechanics
The results demonstrate that DCEM outperforms DEM in terms of stress accuracy and efficiency and has an advantage in dealing with complex displacement boundary conditions, which is supported by theoretical analyses and numerical simulations.
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations
The boundary integral equations are employed to transfer all the unknowns to the boundary, then the unknowns are approximated using neural networks and solved through a training process.
MetaFormer: A Unified Meta Framework for Fine-Grained Recognition
Fine-Grained Visual Classification(FGVC) is the task that requires recognizing the objects belonging to multiple subordinate categories of a super-category.
Ranked #1 on
Fine-Grained Image Classification
on NABirds
(using extra training data)
Computer-aided Recognition and Assessment of a Porous Bioelastomer on Ultrasound Images for Regenerative Medicine Applications
It is difficult using a single traditional image processing algorithm to extract continuous and accurate contour of a porous bioelastomer.
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
The advantage of the proposed method is higher efficiency, more accurate, and less hyperparameters than the strong form PINN with subdomains.
Deep Domain Adaptive Object Detection: a Survey
Deep learning (DL) based object detection has achieved great progress.
Mask Propagation Network for Video Object Segmentation
In this work, we propose a mask propagation network to treat the video segmentation problem as a concept of the guided instance segmentation.
