12 Papers
18 Citations
Bo Meng is an academic researcher from Beijing Institute of Technology. The author has contributed to research in topics: Object detection & Computer science. The author has an hindex of 4, co-authored 12 publications. Previous affiliations of Bo Meng include Chinese Ministry of Public Security & Rensselaer Polytechnic Institute.
Chat about Author
Papers
A Scale Balanced Loss for Bounding Box Regression
TL;DR: The scale balanced loss is proposed, which is asymmetric, position-sensitive, and scale-invariant, and designed as a fraction to eliminate the scale information contained in the numerator and denominator in order to solve the area maze problem.
Model and reconstruction of a K-edge contrast agent distribution with an X-ray photon-counting detector.
TL;DR: A general radon transform is established to link the contrast-agent concentration to X-ray intensity measurement data and an iterative algorithm is proposed to reconstruct a contrast- agent distribution and tissue attenuation background simultaneously.
9
Image reconstruction for x-ray K-edge imaging with a photon counting detector
TL;DR: In this paper, the authors proposed a new K-edge imaging method, which not only quantifies a distribution of a contrast agent, but also provides an optimized contrast ratio for biomedical applications.
7
Complete Video-Level Representations for Action Recognition
TL;DR: A method based on a 3D backbone network for multi scale spatial feature representation, which uses a pyramid pooling layer to allow the input of video frames at different scales, and then aggregates short-term spatial–temporal features into a long-term video-level representation is proposed.
Inference Adaptive Thresholding based Non-Maximum Suppression for Object Detection in Video Image Sequence
Mengqing Jiang,Yurong Jiang,Min Li,Bo Meng,Hong Song,Danni Ai,Jian Yang +6 more
- 15 Mar 2019
TL;DR: Experimental results demonstrate that this simple and unsupervised method outperforms state-of-the-art NMS algorithms, with an increase of 6% in mean average precision (mAP) on the ImageNet VID dataset.
5