-
Chapter and Conference Paper
An Investigation of CNN-CARU for Image Captioning
The goal of an image description is to extract essential information and a description of the content of a media feature from an image. This description can be obtained directly from a human-understandable des...
-
Chapter and Conference Paper
Robust Pedestrian Detection: Faster Deployments with Fusion of Models
Pedestrian detection has a wide range of real-world critical applications including security and management of emergency scenarios. In critical applications, detection recall and precision are both essential ...
-
Chapter and Conference Paper
CARU: A Content-Adaptive Recurrent Unit for the Transition of Hidden State in NLP
This article introduces a novel RNN unit inspired by GRU, namely the Content-Adaptive Recurrent Unit (CARU). The design of CARU contains all the features of GRU but requires fewer training parameters. We make ...
-
Chapter and Conference Paper
Variable-Depth Convolutional Neural Network for Text Classification
This article introduces a recurrent CNN based framework for the classification of arbitrary length text in natural sentence. In our model, we present a complete CNN design with recurrent structure to capture t...
-
Chapter and Conference Paper
Fast Grid-Based Fluid Dynamics Simulation with Conservation of Momentum and Kinetic Energy on GPU
Since the computation of fluid animation is often too heavy to run in real-time simulation, we propose a fast grid-based method with parallel acceleration. In order to reduce the cost of computation kee** a ...