6 papers
Multi-Model Least Squares-Based Recomputation Framework for Large Data Analysis
Wandong Zhang, QM Jonathan Wu, Yimin Yang +3
Most multilayer least squares (LS)-based neural networks are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsu…
Understanding Global Reaction to the Recent Outbreaks of COVID-19: Insights from Instagram Data Analysis
Abdul Muntakim Rafi, Shivang Rana, Rajwinder Kaur +2
The coronavirus disease, also known as the COVID-19, is an ongoing pandemic of a severe acute respiratory syndrome. The pandemic has led to the cancellation of many religious, poli…
Deep Networks with Fast Retraining
Wandong Zhang, Yimin Yang, Jonathan Wu
Recent work [1] has utilized Moore-Penrose (MP) inverse in deep convolutional neural network (DCNN) learning, which achieves better generalization performance over the DCNN with a…
RemNet: Remnant Convolutional Neural Network for Camera Model Identification
Abdul Muntakim Rafi, Thamidul Islam Tonmoy, Uday Kamal +2
Camera model identification (CMI) has gained significant importance in image forensics as digitally altered images are becoming increasingly commonplace. In this paper, a novel con…
Non-iterative recomputation of dense layers for performance improvement of DCNN
Yimin Yang, Q. M. Jonathan Wu, Xiexing Feng +1
An iterative method of learning has become a paradigm for training deep convolutional neural networks (DCNN). However, utilizing a non-iterative learning strategy can accelerate th…
A Feature Embedding Strategy for High-level CNN representations from Multiple ConvNets
Thangarajah Akilan, Q. M. Jonathan Wu, Wei Jiang
Following the rapidly growing digital image usage, automatic image categorization has become preeminent research area. It has broaden and adopted many algorithms from time to time,…