Search Results for author:
Found 9 papers, 3 papers with code
Integrating remote sensing data assimilation, deep learning and large language model for interactive wheat breeding yield prediction
Based on unmanned aerial vehicle remote sensing technology, high-throughput crop phenotyping data in breeding areas is collected to provide data support for the breeding decisions of breeders.
Multi-Scale Representation Learning for Image Restoration with State-Space Model
Image restoration endeavors to reconstruct a high-quality, detail-rich image from a degraded counterpart, which is a pivotal process in photography and various computer vision systems.
Adaptive Frequency Enhancement Network for Single Image Deraining
We employ convolutions of different scales to adaptively decompose image frequency bands, introduce a feature enhancement module to boost the features of different frequency components and present a novel interaction module for interchanging and merging information from various frequency branches.
MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
BP4ER: Bootstrap Prompting for Explicit Reasoning in Medical Dialogue Generation
This approach eliminates the need for entity annotation and increases the transparency of the MDG process by explicitly generating the intermediate reasoning chain.
Dual-Path Coupled Image Deraining Network via Spatial-Frequency Interaction
Transformers have recently emerged as a significant force in the field of image deraining.
EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals
However, challenges such as low signal-to-noise ratio (SNR), high inter-subject variability, and channel mismatch complicate the extraction of robust, universal EEG representations.
Latent Degradation Representation Constraint for Single Image Deraining
Since rain streaks show a variety of shapes and directions, learning the degradation representation is extremely challenging for single image deraining.
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study
We use five dimensionality reduction methods -- PCA, KPCA, ICA, AE, and DAE -- to compress 301-dimensional hyperspectral pixels.
