Abstract: Graph convolutional network (GCN) has shown potential in hyperspectral image (HSI) classification. However, GCN is a transductive learning method, which is difficult to aggregate the new ...

Abstract: Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem ...

"DeepEMD v2: Differentiable Earth Mover's Distance for Few-Shot Learning" (TPAMI Extension). DeepEMD achieves new state-of-the-art performance on five few-shot learning benchmarks with significant ...

A liver cancer diagnosis frequently leads to surgery, with the goal of completely removing all malignant tissue. To ensure ...

Introduction Antimicrobial stewardship efforts in low- and middle-income countries (LMICs) largely focus on qualified ...

Background Accurate assessment of the prevalence of large vessel occlusion (LVO) in patients presenting with acute ischemic stroke (AIS) is critical for optimal resource allocation in neurovascular ...

Explore how AI phenotypic screening transforms image-based drug discovery through advanced phenotypic data analysis and ML-driven cell-based assays.

Dr. techn. Ulrich Krispel ulrich.krispel@fraunhofer.at ...

A set of Roman bronze cauldrons recovered from a German field spent an estimated 1,700 years underground, raising pointed ...

This work presents VoCo, a new method for Large-Scale 3D Medical Image Pre-training. We release a new benchmark, including 160K volumes (42M slices) for pre-training, 31M~1.2B params of pre-trained ...