10 citations · 22 across the 5 of their papers we have counts for
5 papers
Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models
Houze Liu, Tong Zhou, Yanlin Xiang +3
Medical image segmentation is crucial for accurate clinical diagnoses, yet it faces challenges such as low contrast between lesions and normal tissues, unclear boundaries, and high…
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data
Aoran Shen, Minghao Dai, Jiacheng Hu +3
In the 21st-century information age, with the development of big data technology, effectively extracting valuable information from massive data has become a key issue. Traditional…
Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches
Yinqiu Feng, Aoran Shen, Jiacheng Hu +3
This paper presents an innovative approach to enhancing few-shot learning by integrating data augmentation with model fine-tuning in a framework designed to tackle the challenges p…
Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs
Junliang Du, Guiran Liu, Jia Gao +3
This study proposed a knowledge graph entity extraction and relationship reasoning algorithm based on a graph neural network, using a graph convolutional network and graph attentio…
Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis
Junliang Du, Yiru Cang, Tong Zhou +2
This study introduces the Hybrid Multi-modal VGG (HM-VGG) model, a cutting-edge deep learning approach for the early diagnosis of glaucoma. The HM-VGG model utilizes an attention m…