Y
Yuting Zhang
Researcher at Xi'an Jiaotong University
Publications - 5
Citations - 222
Yuting Zhang is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Image retrieval & Sketch. The author has an hindex of 4, co-authored 5 publications receiving 158 citations.
Papers
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Journal ArticleDOI
Enhancing Sketch-Based Image Retrieval by CNN Semantic Re-ranking
TL;DR: A convolutional neural network semantic re-ranking system to enhance the performance of sketch-based image retrieval (SBIR) and achieves significantly higher precision in the top ten different SBIR methods and datasets.
Journal ArticleDOI
Sketch-Based Image Retrieval by Salient Contour Reinforcement
TL;DR: The paper presents a sketch-based image retrieval algorithm that combines an SBIR-based approach by salient contour reinforcement with a new descriptor, namely an angular radial orientation partitioning (AROP) feature that fully utilizes the edge pixels' orientation information in contour maps to identify the spatial relationships.
Journal ArticleDOI
Enhancing Sketch-Based Image Retrieval by Re-Ranking and Relevance Feedback
TL;DR: This approach makes full use of the semantics in query sketches and the top ranked images of the initial results and applies relevance feedback to find more relevant images for the input query sketch and improves the performance of the sketch-based image retrieval.
Proceedings ArticleDOI
Sketch-based image retrieval using contour segments
TL;DR: The paper presents a sketch-based image retrieval algorithm and proposes a new descriptor, namely angular radial orientation partitioning (AROP) feature, which makes full use of the gradient orientation information to decrease the gap between sketch and image.
Book ChapterDOI
Deep Neural Networks for Free-Hand Sketch Recognition
TL;DR: This paper proposes a CNN training on contours that performs well on sketch recognition over different databases of the sketch images and makes some adjustments to the contours for training to reach higher recognition accuracy.