Amanote Research
Register
Sign In
Discover open access scientific publications
Search, annotate, share and cite publications
Publications by Shiyao Jin
Corrigendum to “A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks”
Computational Intelligence and Neuroscience
Medicine
Mathematics
Computer Science
Neuroscience
Related publications
An Automatic Nuclei Segmentation Method Based on Deep Convolutional Neural Networks for Histopathology Images
BMC Biomedical Engineering
DRU Image Semantic Segmentation Using Deep Neural Networks
Journal of Image and Signal Processing
Robust Left Ventricle Segmentation From Ultrasound Data Using Deep Neural Networks and Efficient Search Methods
Mechanics of Wound Closure: Emerging Tape-Based Wound Closure Technology vs. Traditional Methods
Cureus
The Particle Track Reconstruction Based on Deep Neural Networks
EPJ Web of Conferences
Astronomy
Physics
Corrigendum: Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information
Frontiers in Neuroscience
Neuroscience
Triplet Deep Hashing With Joint Supervised Loss Based on Deep Neural Networks
Computational Intelligence and Neuroscience
Medicine
Mathematics
Computer Science
Neuroscience
An Overview of Methods for Deep Learning in Neural Networks
Bulletin of the South Ural State University. Series "Computational Mathematics and Software Engineering"
Corrigendum: A Curiosity-Based Learning Method for Spiking Neural Networks
Frontiers in Computational Neuroscience
Neuroscience
Cellular
Molecular Neuroscience