6 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
Treatment Outcome Prediction for Intracerebral Hemorrhage via Generative Prognostic Model with Imaging and Tabular Data
Wenao Ma, Cheng Chen, Jill Abrigo +6
Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This pa…
Diffusion Model based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification
Shizhan Gong, Cheng Chen, Yuqi Gong +5
Brain midline shift (MLS) is one of the most critical factors to be considered for clinical diagnosis and treatment decision-making for intracranial hemorrhage. Existing computatio…
SM+: Refined Scale Match for Tiny Person Detection
Nan Jiang, Xuehui Yu, Xiaoke Peng +2
Detecting tiny objects ( e.g., less than 20 x 20 pixels) in large-scale images is an important yet open problem. Modern CNN-based detectors are challenged by the scale mismatch bet…
Effective Fusion Factor in FPN for Tiny Object Detection
Yuqi Gong, Xuehui Yu, Yao Ding +3
FPN-based detectors have made significant progress in general object detection, e.g., MS COCO and PASCAL VOC. However, these detectors fail in certain application scenarios, e.g.,…
The 1st Tiny Object Detection Challenge:Methods and Results
Xuehui Yu, Zhenjun Han, Yuqi Gong +22
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a…
Scale Match for Tiny Person Detection
Xuehui Yu, Yuqi Gong, Nan Jiang +2
Visual object detection has achieved unprecedented ad-vance with the rise of deep convolutional neural networks.However, detecting tiny objects (for example tiny per-sons less than…