A small attentional YOLO model for landslide detection from satellite remote sensing images
L Cheng, J Li, P Duan, M Wang - Landslides, 2021 - Springer
The use of high-spatial-resolution remote sensing image technology on mobile and
embedded equipment is an important and effective way for emergency rescue and …
embedded equipment is an important and effective way for emergency rescue and …
Photonics for Neuromorphic Computing: Fundamentals, Devices, and Opportunities
R Li, Y Gong, H Huang, Y Zhou, S Mao… - Advanced …, 2025 - Wiley Online Library
In the dynamic landscape of Artificial Intelligence (AI), two notable phenomena are
becoming predominant: the exponential growth of large AI model sizes and the explosion of …
becoming predominant: the exponential growth of large AI model sizes and the explosion of …
Learning what not to segment: A new perspective on few-shot segmentation
Recently few-shot segmentation (FSS) has been extensively developed. Most previous
works strive to achieve generalization through the meta-learning framework derived from …
works strive to achieve generalization through the meta-learning framework derived from …
Masked diffusion transformer is a strong image synthesizer
Despite its success in image synthesis, we observe that diffusion probabilistic models
(DPMs) often lack contextual reasoning ability to learn the relations among object parts in an …
(DPMs) often lack contextual reasoning ability to learn the relations among object parts in an …
Base and meta: A new perspective on few-shot segmentation
Despite the progress made by few-shot segmentation (FSS) in low-data regimes, the
generalization capability of most previous works could be fragile when countering hard …
generalization capability of most previous works could be fragile when countering hard …
Holistic prototype activation for few-shot segmentation
Conventional deep CNN-based segmentation approaches have achieved satisfactory
performance in recent years, however, they are essentially Big Data-driven technologies …
performance in recent years, however, they are essentially Big Data-driven technologies …
SPNet: Siamese-prototype network for few-shot remote sensing image scene classification
Few-shot image classification has attracted extensive attention, which aims to recognize
unseen classes given only a few labeled samples. Due to the large intraclass variances and …
unseen classes given only a few labeled samples. Due to the large intraclass variances and …
Prototype-CNN for few-shot object detection in remote sensing images
Recently, due to the excellent representation ability of convolutional neural networks
(CNNs), object detection in remote sensing images has undergone remarkable …
(CNNs), object detection in remote sensing images has undergone remarkable …
Class attention network for image recognition
Visual attention has become a popular and widely used component for image recognition.
Although various attention-based methods have been proposed and achieved relatively …
Although various attention-based methods have been proposed and achieved relatively …
Global rectification and decoupled registration for few-shot segmentation in remote sensing imagery
Few-shot segmentation (FSS), which aims to determine specific objects in the query image
given only a handful of densely labeled samples, has received extensive academic attention …
given only a handful of densely labeled samples, has received extensive academic attention …