Experimental results on fetal brain MRI dataset show that our proposed model achieves superior performance, and outperforms several state-of-the-art methods.Zhang, XukunCui, ZhimingChen, ChanganWei, JieLou, JingjiaoHu, WenxinZhang, HeZhou, TaoShi, FengShen, DinggangSpringer, Cham...
网络主要包含两个模块:伪装目标检测网络(camouflaged object detection network)和置信度估计网络(confidence estimation network) 伪装目标检测网络 该部分网络采用ResNet-50作为编码器产生特征图Fi {i=1,...,5},F3-F5 使用融合模块(Fusion Module,FM)来组合不同层次的特征,输出为 fθini=yθini 作为初始预测,F2...
Implementation of our AAAI2022 paper, Show Your Faith: Cross-Modal Confidence-Aware Network for Image-Text Matching. - CrossmodalGroup/CMCAN
然后,一个策略网络(policy network)从场景补全结果和置信度图中推断出动作。我们的实验表明,所提出的场景补全模块提高了下游导航策略的效率。 1. 引言 Introduction 本文讨论了视觉语义导航(visual semantic navigation)的任务,特别是ObjectNav[1],其目标是,给定了第一人称RGB-D图像观测(如图1所示),将机器人(朝向...
Wavelet neural network model for reservoir inflow prediction (WNN) model is proposed for monthly reservoir inflow prediction by combining the Discrete Wavelet Transform (DWT) and Levenberg-Marquardt optimization algorithm... Okkan,U. - 《Scientia Iranica》 被引量: 59发表: 2012年 Knee Joint Secondary...
The proposed network architecture. The network in the training phase (top) consists of a stereo vision-based self-supervisory signal module that provides disparity and its confidence as self-supervisory signals, a monocular depth estimation module that actually performs the learning, and a newly desig...
A camouflaged object detection network is designed to produce our camouflage prediction. Then, we concatenate it with the input image and feed it to the confidence estimation network to produce an one channel confidence map.We generate dynamic supervision for the confidence estimation network, ...
We report the classification performance and calibration performance with the ECE for two network architectures: ResNet50 and DenseNet121. Model Accuracy ECE↓ Baseline ResNet50 68.16 0.2063 Ours P-CBLS 71.76 0.0955 Ours ts_P-CBLS 71.80 0.1630 Ours ls_P-CBLS 70.67 0.0726 Baseline DenseNet121 ...
Specifically, we introduce a Confidence-Aware Semantic Matching Network (CAMNet) which instantiates two key ideas of our approach. First, we propose to estimate a dense confidence map for a matching prediction through self-supervised learning. Second, based on the estimated confidence, we refine ...
In this study, we present a method based on Monte Carlo Dropout (MCD)asBayesian neural network (BNN) approximationfor confidence-aware severity classification of lung diseases in COVID-19 patients using chest X-rays (CXRs). Trained and tested on 1208 CXRs from Hospital 1 in the USA, the ...