73 citations · 289 across the 37 of their papers we have counts for
6 papers · 2 filters
ResizeMix: Mixing Data with Preserved Object Information and True Labels
Jie Qin, Jiemin Fang, Qian Zhang +3
Data augmentation is a powerful technique to increase the diversity of data, which can effectively improve the generalization ability of neural networks in image recognition tasks.…
Contour Primitive of Interest Extraction Network Based on One-Shot Learning for Object-Agnostic Vision Measurement
Fangbo Qin, Jie Qin, Siyu Huang +1
Image contour based vision measurement is widely applied in robot manipulation and industrial automation. It is appealing to realize object-agnostic vision system, which can be con…
Auto-Encoding Twin-Bottleneck Hashing
Yuming Shen, Jie Qin, Jiaxin Chen +5
Conventional unsupervised hashing methods usually take advantage of similarity graphs, which are either pre-computed in the high-dimensional space or obtained from random anchor po…
Layer-wise Conditioning Analysis in Exploring the Learning Dynamics of DNNs
Lei Huang, Jie Qin, Li Liu +2
Conditioning analysis uncovers the landscape of an optimization objective by exploring the spectrum of its curvature matrix. This has been well explored theoretically for linear mo…
Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition
Zhao Zhang, Zemin Tang, Zheng Zhang +3
The Deep Convolutional Neural Networks (CNNs) have obtained a great success for pattern recognition, such as recognizing the texts in images. But existing CNNs based frameworks sti…
Dense Residual Network: Enhancing Global Dense Feature Flow for Character Recognition
Zhao Zhang, Zemin Tang, Yang Wang +4
Deep Convolutional Neural Networks (CNNs), such as Dense Convolutional Networks (DenseNet), have achieved great success for image representation by discovering deep hierarchical in…