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Found 14 papers, 4 papers with code
Artificial intelligence for partial differential equations in computational mechanics: A review
In AI for Science, using artificial intelligence algorithms to solve partial differential equations (AI for PDEs: Artificial intelligence for partial differential equations) has become a focal point in computational mechanics.
Two Stage Segmentation of Cervical Tumors using PocketNet
Cervical cancer remains the fourth most common malignancy amongst women worldwide. 1 Concurrent chemoradiotherapy (CRT) serves as the mainstay definitive treatment regimen for locally advanced cervical cancers and includes external beam radiation followed by brachytherapy. 2 Integral to radiotherapy treatment planning is the routine contouring of both the target tumor at the level of the cervix, associated gynecologic anatomy and the adjacent organs at risk (OARs).
Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov Arnold Networks
AI for partial differential equations (PDEs) has garnered significant attention, particularly with the emergence of Physics-informed neural networks (PINNs).
Multiple Integration Model for Single-source Domain Generalizable Person Re-identification
In this paper, a novel MulTiple Integration (MTI) model is introduced for single-source DG person re-ID.
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: 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.
