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Found 18 papers, 3 papers with code
Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models
Medical image segmentation plays an important role in many image-guided clinical approaches.
Task-Driven Exploration: Decoupling and Inter-Task Feedback for Joint Moment Retrieval and Highlight Detection
Video moment retrieval and highlight detection are two highly valuable tasks in video understanding, but until recently they have been jointly studied.
AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation
However, we argue that the current design of the vision transformer-based UNet (ViT-UNet) segmentation models may not effectively handle the heterogeneous appearance (e. g., varying shapes and sizes) of objects of interest in medical image segmentation tasks.
Ranked #2 on
Medical Image Segmentation
on ACDC
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation
D-Net is able to effectively utilize a multi-scale large receptive field and adaptively harness global contextual information.
Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ Segmentation
We evaluated Dynamic U-Net in two abdominal multi-organ segmentation benchmarks.
Optimally Coordinated Energy Management Framework for Profit Maximization Considering Dispatchable and Non-Dispatchable Energy Resources
Contemporary distribution network can be seen with diverse dispatchable and non-dispatchable energy resources.
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development
In the first component, we introduce a theoretical function-preserving transformation of recurrent neural networks (RNN) to the literature for capturing the hidden temporal patterns within the time-series data.
A Highly Configurable Hardware/Software Stack for DNN Inference Acceleration
We have enhanced the VTA design space and enabled end-to-end support for additional workloads.
Robust wavefront dislocations of Friedel oscillations in gapped graphene
Friedel oscillation is a well-known wave phenomenon, which represents the oscillatory response of electron waves to imperfection.
Mesoscale and Nanoscale Physics
Site-resolved imaging of ultracold fermions in a triangular-lattice quantum gas microscope
Quantum gas microscopes have expanded the capabilities of quantum simulation of Hubbard models by enabling the study of spatial spin and density correlations in square lattices.
Quantum Gases Atomic Physics
Model Synthesis for Communication Traces of System-on-Chip Designs
In this paper, we consider the problem of inferring models from communication traces of system-on-chip~(SoC) designs.
Reconfigurable Intelligent Surface: Design the Channel -- a New Opportunity for Future Wireless Networks
In this paper, we survey state-of-the-art research outcomes in the burgeoning field of reconfigurable intelligent surface (RIS) in view of its potential for significant performance enhancement for next generation wireless communication networks by means of adapting the propagation environment.
Deep Reinforcement Learning with a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning
Extensive experiments show that the soft stage incentive reward function is able to improve the convergence rate by up to 46. 9% with the state-of-the-art DRL methods.
Two-stage short-term wind power forecasting algorithm using different feature-learning models
Considering the overfitting issue, we propose a new moving window-based algorithm using a validation set in the first stage to update the training data in both stages with two different moving window processes. Experiments were conducted at three wind farms, and the results demonstrate that the model with single input multiple output structure obtains better forecasting accuracy compared to existing models.
Mining Message Flows using Recurrent Neural Networks for System-on-Chip Designs
Initial results show that the proposed approach is capable of extracting various patterns on system-level specifications from the highly concurrent SoC execution traces.
Single upper limb pose estimation method based on improved stacked hourglass network
Using the stacked hourglass network model, a single-person upper limb skeleton key point detection model was designed. Deconvolution was employed to replace the up-sampling operation of the hourglass module in the original model, solving the problem of rough feature maps.
Sim-to-Real Optimization of Complex Real World Mobile Network with Imperfect Information via Deep Reinforcement Learning from Self-play
Mobile network that millions of people use every day is one of the most complex systems in the world.
SYSTRAN's Pure Neural Machine Translation Systems
Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by several entities announcing roll-out of NMT engines to replace their existing technologies.
