8 papers · 1 filter
Phase-Aware Spatial-Frequency Fusion for Few-Shot Fine-Grained Image Classification
Ruiling Liu, Linyue Zhang, Wenyi Zeng +5
Few-shot fine-grained image classification (FSFGIC) aims to classify similar images with limited labeled examples. This work highlights the critical yet underutilized role of phase…
GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction
Boyu Yuan, Jiamiao Lu, Weichuan Zhang +5
This study introduces an automated deep learning framework for predicting brain injury (BI) in preterm infants from T2-weighted MRI (dHCP dataset). We propose GloResNet, a lightwei…
Adaptive receptive field-based spatial-frequency feature reconstruction network for fine-grained few-shot image classification
Linyue Zhang, Wenyi Zeng, Zicheng Pan +6
Feature reconstruction techniques are widely applied for few-shot fine-grained image classification (FSFGIC). Our research indicates that one of the main challenges facing existing…
Meningioma Analysis and Diagnosis using Limited Labeled Samples
Jiamiao Lu, Wei Wu, Ke Gao +8
The biological behavior and treatment response of meningiomas depend on their grade, making an accurate diagnosis essential for treatment planning and prognosis assessment. We obse…
Deep learning-based neurodevelopmental assessment in preterm infants
Lexin Ren, Jiamiao Lu, Weichuan Zhang +6
Preterm infants (born between 28 and 37 weeks of gestation) face elevated risks of neurodevelopmental delays, making early identification crucial for timely intervention. While dee…
Second-order Gaussian directional derivative representations for image high-resolution corner detection
Jiamiao Lu, Dongbo Xie, Junjie Qiu +3
Corner detection is widely used in various computer vision tasks, such as image matching and 3D reconstruction. Our research indicates that there are theoretical flaws in Zhang et…
Feature Complementation Architecture for Visual Place Recognition
Weiwei Wang, Meijia Wang, Haoyi Wang +5
Visual place recognition (VPR) plays a crucial role in robotic localization and navigation. The key challenge lies in constructing feature representations that are robust to enviro…
A novel spatial-frequency domain network for zero-shot incremental learning
Jie Ren, Yang Zhao, Weichuan Zhang +1
Zero-shot incremental learning aims to enable the model to generalize to new classes without forgetting previously learned classes. However, the semantic gap between old and new sa…