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Found 9 papers, 2 papers with code
ElasticLaneNet: An Efficient Geometry-Flexible Approach for Lane Detection
The task of lane detection involves identifying the boundaries of driving areas in real-time.
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale
Popular guidance for denoising diffusion probabilistic model (DDPM) linearly combines distinct conditional models together to provide enhanced control over samples.
Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception
Urban segmentation and lane detection are two important tasks for traffic scene perception.
Energy stable neural network for gradient flow equations
In this paper, we propose an energy stable network (EStable-Net) for solving gradient flow equations.
Large Transformers are Better EEG Learners
The proposed approach allows for seamless integration of pre-trained vision models and language models in time series decoding tasks, particularly in EEG data analysis.
DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator Splitting
Deep neural networks (DNNs) recently emerged as a promising tool for analyzing and solving complex differential equations arising in science and engineering applications.
GOLLIC: Learning Global Context beyond Patches for Lossless High-Resolution Image Compression
Besides the latent variable unique to each patch, we introduce shared latent variables between patches to construct the global context.
Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks
Pruning is a model compression method that removes redundant parameters in deep neural networks (DNNs) while maintaining accuracy.
An Elastic Interaction-Based Loss Function for Medical Image Segmentation
The commonly used loss functions in the deep segmentation task are pixel-wise loss functions.
