Wound intensity correction and segmentation with convolutional neural networks
By Bin Li, Junwu Zhu, Yujie Li, Yun Li, Xing Xu, Li He, Xin Li, Jianru Li, Seiichi Serikawa. 2017
209 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism, Occupational Therapy
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Yujie Li
- Hyoungseop Kim
- Yuehan Chen
- Chunquan Liang
- Seiichi Serikawa
- Peng Jiang
- Min Chen
- Marcin Hernes
Citations in the corpus
- Deep learning for financial time series forecasting in A-Trader system (2017, methodology): “CNNs are variations of MLP designed to use minimal amounts of preprocessing [29].”
- Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks (2019, background): “The first few layers of a convolutional neural network typically extract the color and corner features [32], [33] and it is of little value to utilize Inception to extract these features.”
- Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learning (2018, methodology): “In future, we will consider implementing deep learning methods [6], [7], [11]–[14] to select the threshold temperature.”
- Brain Intelligence: Go beyond Artificial Intelligence (2017, background): “Brain Intelligence (BI) There are many approaches [58-61] proposed to solve the limitations of recent AI.”