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Found 5 papers, 5 papers with code
FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
Automatic lung image segmentation assists doctors in identifying diseases such as lung cancer, COVID-19, and respiratory disorders.
Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer Approach
Our method introduces a lightweight transformer-enhanced TransUNet for precise lung segmentation, achieving a Dice score of 95. 68% on the "Chest X-ray Masks and Labels" dataset with fewer parameters than traditional transformers.
Ranked #1 on
Classification
on COVID-19 Image Data Collection
ABANet: Attention boundary-aware network for image segmentation
Our dataset of masked faces with mask region labels and source code will be available online.
Ranked #1 on
Segmentation
on MFSD
Advancing Multilingual Handwritten Numeral Recognition with Attention-driven Transfer Learning
In this work, we present a robust and cost-effective approach that handles multilingual handwritten numeral recognition across a wide range of languages.
Handwritten Digit Recognition
Optical Character Recognition
+1
RAT: Reinforcement-Learning-Driven and Adaptive Testing for Vulnerability Discovery in Web Application Firewalls
In practice, using a brute-force attack to discover vulnerabilities is infeasible due to the wide variety of attack patterns.
