133 citations · 152 across the 9 of their papers we have counts for
9 papers
Compacting, Picking and Growing for Unforgetting Continual Learning
Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu +3
Continual lifelong learning is essential to many applications. In this paper, we propose a simple but effective approach to continual deep learning. Our approach leverages the prin…
IMMVP: An Efficient Daytime and Nighttime On-Road Object Detector
Cheng-En Wu, Yi-Ming Chan, Chien-Hung Chen +2
It is hard to detect on-road objects under various lighting conditions. To improve the quality of the classifier, three techniques are used. We define subclasses to separate daytim…
Learning Conditional Random Fields with Augmented Observations for Partially Observed Action Recognition
Shih-Yao Lin, Yen-Yu Lin, Chu-Song Chen +1
This paper aims at recognizing partially observed human actions in videos. Action videos acquired in uncontrolled environments often contain corrupt frames, which make actions part…
Data-specific Adaptive Threshold for Face Recognition and Authentication
Hsin-Rung Chou, Jia-Hong Lee, Yi-Ming Chan +1
Many face recognition systems boost the performance using deep learning models, but only a few researches go into the mechanisms for dealing with online registration. Although we c…
Stingray Detection of Aerial Images Using Augmented Training Images Generated by A Conditional Generative Model
Yi-Min Chou, Chien-Hung Chen, Keng-Hao Liu +1
In this paper, we present an object detection method that tackles the stingray detection problem based on aerial images. In this problem, the images are aerially captured on a sea-…
Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications
Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen +1
Automatic age and gender classification based on unconstrained images has become essential techniques on mobile devices. With limited computing power, how to develop a robust syste…
Unifying and Merging Well-trained Deep Neural Networks for Inference Stage
Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee +2
We propose a novel method to merge convolutional neural-nets for the inference stage. Given two well-trained networks that may have different architectures that handle different ta…
To Know Where We Are: Vision-Based Positioning in Outdoor Environments
Kuan-Wen Chen, Chun-Hsin Wang, Xiao Wei +4
Augmented reality (AR) displays become more and more popular recently, because of its high intuitiveness for humans and high-quality head-mounted display have rapidly developed. To…
Bayesian Fisher's Discriminant for Functional Data
Yao-Hsiang Yang, Lu-Hung Chen, Chieh-Chih Wang +1
We propose a Bayesian framework of Gaussian process in order to extend Fisher's discriminant to classify functional data such as spectra and images. The probability structure for o…