51 citations · 205 across the 29 of their papers we have counts for
5 papers · 1 filter
Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data
Christian Bartz, Hendrik Raetz, Jona Otholt +2
One of the most pressing problems in the automated analysis of historical documents is the availability of annotated training data. The problem is that labeling samples is a time-c…
BoolNet: Minimizing The Energy Consumption of Binary Neural Networks
Nianhui Guo, Joseph Bethge, Haojin Yang +4
Recent works on Binary Neural Networks (BNNs) have made promising progress in narrowing the accuracy gap of BNNs to their 32-bit counterparts. However, the accuracy gains are often…
Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge
Ziyun Li, Xinshao Wang, Di Hu +4
Mutual knowledge distillation (MKD) improves a model by distilling knowledge from another model. However, \textit{not all knowledge is certain and correct}, especially under advers…
AsymmNet: Towards ultralight convolution neural networks using asymmetrical bottlenecks
Haojin Yang, Zhen Shen, Yucheng Zhao
Deep convolutional neural networks (CNN) have achieved astonishing results in a large variety of applications. However, using these models on mobile or embedded devices is difficul…
Evaluating Post-Training Compression in GANs using Locality-Sensitive Hashing
Gonçalo Mordido, Haojin Yang, Christoph Meinel
The analysis of the compression effects in generative adversarial networks (GANs) after training, i.e. without any fine-tuning, remains an unstudied, albeit important, topic with t…