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Peng Wang

4 papers hereh-index 324.8k citations51 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Peng Wang — 20 papers, h 32
  • Peng Wang — 8 papers
  • Peng Wang — 7 papers, h 7
  • Peng Wang — 6 papers, h 16
  • Peng Wang — 4 papers, h 29
  • Peng Wang — 4 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132017
most citedTowards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

40 citations · 56 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2017★ 16 cited

Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning

Qi Wu, Peng Wang, Chunhua Shen +2

The Visual Dialogue task requires an agent to engage in a conversation about an image with a human. It represents an extension of the Visual Question Answering task in that the age…

cs.CV2017★ 40 cited

Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

Hui Li, Peng Wang, Chunhua Shen

In this work, we tackle the problem of car license plate detection and recognition in natural scene images. We propose a unified deep neural network which can localize license plat…

cs.CV2016

Pushing the Limits of Deep CNNs for Pedestrian Detection

Qichang Hu, Peng Wang, Chunhua Shen +2

Compared to other applications in computer vision, convolutional neural networks have under-performed on pedestrian detection. A breakthrough was made very recently by using sophis…

cs.CV2013

Training Effective Node Classifiers for Cascade Classification

Chunhua Shen, Peng Wang, Sakrapee Paisitkriangkrai +1

Cascade classifiers are widely used in real-time object detection. Different from conventional classifiers that are designed for a low overall classification error rate, a classifi…

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