2 citations · 3 across the 5 of their papers we have counts for
5 papers
EFCNet: Every Feature Counts for Small Medical Object Segmentation
Lingjie Kong, Qiaoling Wei, Chengming Xu +2
This paper explores the segmentation of very small medical objects with significant clinical value. While Convolutional Neural Networks (CNNs), particularly UNet-like models, and r…
Double A3C: Deep Reinforcement Learning on OpenAI Gym Games
Yangxin Zhong, Jiajie He, Lingjie Kong
Reinforcement Learning (RL) is an area of machine learning figuring out how agents take actions in an unknown environment to maximize its rewards. Unlike classical Markov Decision…
Generative Models for 3D Point Clouds
Lingjie Kong, Pankaj Rajak, Siamak Shakeri
Point clouds are rich geometric data structures, where their three dimensional structure offers an excellent domain for understanding the representation learning and generative mod…
From Audio to Symbolic Encoding
Shenli Yuan, Lingjie Kong, Jiushuang Guo
Automatic music transcription (AMT) aims to convert raw audio to symbolic music representation. As a fundamental problem of music information retrieval (MIR), AMT is considered a d…
Path Integral Based Convolution and Pooling for Heterogeneous Graph Neural Networks
Lingjie Kong, Yun Liao
Graph neural networks (GNN) extends deep learning to graph-structure dataset. Similar to Convolutional Neural Networks (CNN) using on image prediction, convolutional and pooling la…