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Chapter and Conference Paper
DMTP: Controlling Spam Through Message Delivery Differentiation
Unsolicited commercial email, commonly known as spam, has become a pressing problem in today’s Internet. In this paper we re-examine the architectural foundations of the current email delivery system that are ...
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Chapter and Conference Paper
A Coding Hierarchy Computing Based Clustering Algorithm
In actual databases, there are a lot of hierarchy coding data, existing clustering algorithms don’t consider the special treatment of these data structure, so lead nonideal performance and clustering result. T...
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Chapter and Conference Paper
VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results
The Vision Meets Drone Object Detection in Image Challenge (VisDrone-DET 2020) is the third annual object detector benchmarking activity. Compared with the previous VisDrone-DET 2018 and VisDrone-DET 2019 chal...
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Chapter and Conference Paper
VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results
The Vision Meets Drone (VisDrone2020) Multiple Object Tracking (MOT) is the third annual UAV MOT tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer...
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Chapter and Conference Paper
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algori...
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Chapter and Conference Paper
External Knowledge-Based Weakly Supervised Learning Approach on Chinese Clinical Named Entity Recognition
Automatic extraction of clinical named entities, such as body parts, drugs and surgeries, has been of great significance to understand clinical texts. Deep neural networks approaches have achieved remarkable s...
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Chapter and Conference Paper
Efficient Dual-Process Cognitive Recommender Balancing Accuracy and Diversity
In this paper, we propose a dual-process cognitive recommendation system for sequential recommendations. The framework includes an intuitive representation module (System 1) and an inference module (System 2)....