37 citations · 67 across the 5 of their papers we have counts for
6 papers · 1 filter
Efficient Neural Network Approaches for Leather Defect Classification
Sze-Teng Liong, Y. S. Gan, Kun-Hong Liu +5
Genuine leather, such as the hides of cows, crocodiles, lizards and goats usually contain natural and artificial defects, like holes, fly bites, tick marks, veining, cuts, wrinkles…
Integrated Neural Network and Machine Vision Approach For Leather Defect Classification
Sze-Teng Liong, Y. S. Gan, Yen-Chang Huang +2
Leather is a type of natural, durable, flexible, soft, supple and pliable material with smooth texture. It is commonly used as a raw material to manufacture luxury consumer goods f…
Evaluation of the Spatio-Temporal features and GAN for Micro-expression Recognition System
Sze-Teng Liong, Y. S. Gan, Danna Zheng +5
Owing to the development and advancement of artificial intelligence, numerous works were established in the human facial expression recognition system. Meanwhile, the detection and…
Automatic Defect Segmentation on Leather with Deep Learning
Sze-Teng Liong, Y. S. Gan, Yen-Chang Huang +2
Leather is a natural and durable material created through a process of tanning of hides and skins of animals. The price of the leather is subjective as it is highly sensitive to it…
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition
Sze-Teng Liong, Y. S. Gan, John See +2
In the recent year, state-of-the-art for facial micro-expression recognition have been significantly advanced by deep neural networks. The robustness of deep learning has yielded p…
Automatic Surface Area and Volume Prediction on Ellipsoidal Ham using Deep Learning
Y. S. Gan, Sze-Teng Liong, Yen-Chang Huang
This paper presents novel methods to predict the surface and volume of the ham through a camera. This implies that the conventional weight measurement to obtain in the object's vol…