在本论文中,我们提出了一种高效的比较句子相似性的方法 Enhanced-RCNN,这是我们在经典文本匹配模型 ESIM的基础上改进的模型,该模型在 Quora Question Pair 和 Ant Financial 两个公开的文本匹配数据集上均取得了非常有竞争力的结果,并且和时下火热的预训练语言模型 BERT 相比,Enhanced-RCNN 也取得了相当的效果,同...
我们在经典的文本匹配模型 ESIM 的基础上,提出了一种新型的计算文本相似度的方法 Enhanced-RCNN,在效果保证的前提下也拥有良好的性能。 下面将对 Enhanced-RCNN 模型进行详细的介绍。 三、Enhanced-RCNN Model Enhanced-RCNN 模型的结构如下图所示,我们自底向上依次来介绍: Enhanced-RCNN 模型整体结构图 3.1 Inpu...
We needed to look at the average performance of a traffic sign recognition system employing upgraded CNN architecture, and we discovered that detection performance can drop dramatically under difficult conditions. Enhance precision and accuracy in difficult weather conditions such as snow, haze, rain, ...
Lightweight Image Super-Resolution with Enhanced CNN(LESRCNN)is conducted by Chunwei Tian, Ruibin Zhuge, Zhihao Wu, Yong Xu, Wangmeng Zuo, Chen Chen and Chia-Wen Lin, and accepted by Knowledge-Based Systems (IF:8.139) in 2020. It is implemented by Pytorch. And it is reported by Cver ...
在本论文中,我们提出了一种高效的比较句子相似性的方法 Enhanced-RCNN,这是我们在经典文本匹配模型 ESIM的基础上改进的模型,该模型在 Quora Question Pair 和 Ant Financial 两个公开的文本匹配数据集上均取得了非常有竞争力的结果,并且和时下火热的预训练语言模型 BERT 相比,Enhanced-RCNN 也取得了相当的效果,同...
The enhancement method is based on a cascade Faster R-CNN with Gabor filters and the nave Bayes model, in which the initial bounding boxes of the eye region are detected using Faster R-CNN and the decision step is carried out using Gabor filters and the nave Bayes model to determine which...
在本论文中,我们提出了一种高效的比较句子相似性的方法 Enhanced-RCNN,这是我们在经典文本匹配模型 ESIM的基础上改进的模型,该模型在 Quora Question Pair 和 Ant Financial 两个公开的文本匹配数据集上均取得了非常有竞争力的结果,并且和时下火热的预训练语言模型 BERT 相比,Enhanced-RCNN 也取得了相当的效果,同...
To address this, an enhanced Mask R-CNN model was proposed for multiple objects instance segmentation to support indistinct boundaries and irregular shapes of cattle bodies for precision livestock farming. The contributions of this method are in multiple folds: 1) optimal filter size small...
Multi-ObjectObject RecognitionMachine LearningR-CNNSurveillance.Multi-object recognition is emerging as a technology that can be applied to various real worlds such as image security, gesture recognition, robot vision, and human robot interaction, and it is difficult to recognize public objects in a ...
We also adjusted the R-CNN pooling layer in our suggested model to enable efficient processing of feature maps, which has a major benefit in lowering the unfavorable effects of the R-CNN structure and raising prediction accuracy. The performance of enhanced R- CNN is verified on visual studio ...