60 citations · 171 across the 9 of their papers we have counts for
8 papers · 1 filter
Exploring Text-Guided Single Image Editing for Remote Sensing Images
Fangzhou Han, Lingyu Si, Zhizhuo Jiang +5
Artificial intelligence generative content (AIGC) has significantly impacted image generation in the field of remote sensing. However, the equally important area of remote sensing…
Cartoondiff: Training-free Cartoon Image Generation with Diffusion Transformer Models
Feihong He, Gang Li, Lingyu Si +4
Image cartoonization has attracted significant interest in the field of image generation. However, most of the existing image cartoonization techniques require re-training models u…
Background Debiased SAR Target Recognition via Causal Interventional Regularizer
Hongwei Dong, Fangzhou Han, Lingyu Si +2
Recent studies have utilized deep learning (DL) techniques to automatically extract features from synthetic aperture radar (SAR) images, which shows great promise for enhancing the…
A Dimensional Structure based Knowledge Distillation Method for Cross-Modal Learning
Lingyu Si, Hongwei Dong, Wenwen Qiang +5
Due to limitations in data quality, some essential visual tasks are difficult to perform independently. Introducing previously unavailable information to transfer informative dark…
Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images
Lamei Zhang, Siyu Zhang, Bin Zou +1
Deep learning and convolutional neural networks (CNNs) have made progress in polarimetric synthetic aperture radar (PolSAR) image classification over the past few years. However, a…
Automatic Design of CNNs via Differentiable Neural Architecture Search for PolSAR Image Classification
Hongwei Dong, Siyu Zhang, Bin Zou +1
Convolutional neural networks (CNNs) have shown good performance in polarimetric synthetic aperture radar (PolSAR) image classification due to the automation of feature engineering…
Band Attention Convolutional Networks For Hyperspectral Image Classification
Hongwei Dong, Lamei Zhang, Bin Zou
Redundancy and noise exist in the bands of hyperspectral images (HSIs). Thus, it is a good property to be able to select suitable parts from hundreds of input bands for HSIs classi…
Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework
Lamei Zhang, Hongwei Dong, Bin Zou
Convolutional neural networks (CNNs) have been widely used to improve the accuracy of polarimetric synthetic aperture radar (PolSAR) image classification. However, in most studies,…