69 citations · 160 across the 9 of their papers we have counts for
9 papers
Automatic Intent-Slot Induction for Dialogue Systems
Zengfeng Zeng, Dan Ma, Haiqin Yang +2
Automatically and accurately identifying user intents and filling the associated slots from their spoken language are critical to the success of dialogue systems. Traditional metho…
An Automated Machine Learning (AutoML) Method for Driving Distraction Detection Based on Lane-Keeping Performance
Chen Chai, Juanwu Lu, Xuan Jiang +2
With the enrichment of smartphones, driving distractions caused by phone usages have become a threat to driving safety. A promising way to mitigate driving distractions is to detec…
Automatic Clustering for Unsupervised Risk Diagnosis of Vehicle Driving for Smart Road
Xiupeng Shi, Yiik Diew Wong, Chen Chai +3
Early risk diagnosis and driving anomaly detection from vehicle stream are of great benefits in a range of advanced solutions towards Smart Road and crash prevention, although ther…
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification
Yue Ma, Zengfeng Zeng, Dawei Zhu +5
This paper describes our approach in DSTC 8 Track 4: Schema-Guided Dialogue State Tracking. The goal of this task is to predict the intents and slots in each user turn to complete…
Multi Scale Supervised 3D U-Net for Kidney and Tumor Segmentation
Wenshuai Zhao, Zengfeng Zeng
U-Net has achieved huge success in various medical image segmentation challenges. Kinds of new architectures with bells and whistles might succeed in certain dataset when employed…
Graph Convolutional Neural Networks for Polymers Property Prediction
Minggang Zeng, Jatin Nitin Kumar, Zeng Zeng +3
A fast and accurate predictive tool for polymer properties is demanding and will pave the way to iterative inverse design. In this work, we apply graph convolutional neural network…
End-to-End Video Classification with Knowledge Graphs
Fang Yuan, Zhe Wang, Jie Lin +4
Video understanding has attracted much research attention especially since the recent availability of large-scale video benchmarks. In this paper, we address the problem of multi-l…
Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
Zhe Wang, Kingsley Kuan, Mathieu Ravaut +13
The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% o…
Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge
Kingsley Kuan, Mathieu Ravaut, Gaurav Manek +7
We present a deep learning framework for computer-aided lung cancer diagnosis. Our multi-stage framework detects nodules in 3D lung CAT scans, determines if each nodule is malignan…