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20182023
most citedWhen Machine Learning Meets Quantum Computers: A Case Study

25 citations · 157 across the 23 of their papers we have counts for

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15 papers · 1 filter

cs.CV2020

Interpretable Visual Reasoning via Induced Symbolic Space

Zhonghao Wang, Kai Wang, Mo Yu +4

We study the problem of concept induction in visual reasoning, i.e., identifying concepts and their hierarchical relationships from question-answer pairs associated with images; an…

cs.CV2020

Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation

Zhonghao Wang, Yunchao Wei, Rogerior Feris +4

Learning segmentation from synthetic data and adapting to real data can significantly relieve human efforts in labelling pixel-level masks. A key challenge of this task is how to a…

cs.CV2020

Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

Zhonghao Wang, Mo Yu, Yunchao Wei +5

We consider the problem of unsupervised domain adaptation for semantic segmentation by easing the domain shift between the source domain (synthetic data) and the target domain (rea…

cs.CV2019

SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

Xiaofan Zhang, Haoming Lu, Cong Hao +9

Object detection and tracking are challenging tasks for resource-constrained embedded systems. While these tasks are among the most compute-intensive tasks from the artificial inte…

cs.CV2019

SPGNet: Semantic Prediction Guidance for Scene Parsing

Bowen Cheng, Liang-Chieh Chen, Yunchao Wei +6

Multi-scale context module and single-stage encoder-decoder structure are commonly employed for semantic segmentation. The multi-scale context module refers to the operations to ag…

cs.CV201920 cited

SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection

Xiaofan Zhang, Cong Hao, Haoming Lu +9

Developing artificial intelligence (AI) at the edge is always challenging, since edge devices have limited computation capability and memory resources but need to meet demanding re…