13 citations · 20 across the 4 of their papers we have counts for
4 papers
One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective
Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang +3
A deep hashing model typically has two main learning objectives: to make the learned binary hash codes discriminative and to minimize a quantization error. With further constraints…
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
Ding Sheng Ong, Chee Seng Chan, Kam Woh Ng +2
Ever since Machine Learning as a Service (MLaaS) emerges as a viable business that utilizes deep learning models to generate lucrative revenue, Intellectual Property Right (IPR) ha…
Digital Passport: A Novel Technological Strategy for Intellectual Property Protection of Convolutional Neural Networks
Lixin Fan, KamWoh Ng, Chee Seng Chan
In order to prevent deep neural networks from being infringed by unauthorized parties, we propose a generic solution which embeds a designated digital passport into a network, and…
A Universal Logic Operator for Interpretable Deep Convolution Networks
KamWoh Ng, Lixin Fan, Chee Seng Chan
Explaining neural network computation in terms of probabilistic/fuzzy logical operations has attracted much attention due to its simplicity and high interpretability. Different cho…