M
Meng Li
Researcher at University of Queensland
Publications - 4
Citations - 35
Meng Li is an academic researcher from University of Queensland. The author has contributed to research in topics: Object detection & Artificial neural network. The author has an hindex of 3, co-authored 4 publications receiving 14 citations.
Papers
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Journal ArticleDOI
SID: Incremental learning for anchor-free object detection via Selective and Inter-related Distillation
TL;DR: A novel incremental learning paradigm called Selective and Inter-related Distillation (SID) is proposed and a novel evaluation metric is proposed to better assess the performance of detectors under incremental learning conditions.
Posted Content
Deep Instance-Level Hard Negative Mining Model for Histopathology Images
TL;DR: Zhang et al. as discussed by the authors proposed a deep convolutional neural network (CNN) model that addresses the primary task of a bag classification on a WSI and also learns to identify the response of each instance to provide interpretable results to the final prediction.
Book ChapterDOI
Deep Instance-Level Hard Negative Mining Model for Histopathology Images
TL;DR: A deep convolutional neural network model is proposed that addresses the primary task of a bag classification on a WSI and also learns to identify the response of each instance to provide interpretable results to the final prediction.
Posted Content
SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation
TL;DR: In this paper, a novel incremental learning paradigm called Selective and Inter-related Distillation (SID) is proposed to deal with the challenges of incremental learning on anchor-free object detectors.