Local Character-level Feature Selection 利用宽度为3的卷积核进行卷积 Global Word-level Feature Selection 使用简单的点乘注意力进行自注意力计算 Local Word-level Feature Selection 通过最大池化操作选择突出特征 Multi-level Feature Fusion \lambda_{i}控制每一个特征的重要程度,是个trade-off参数,并且随机初始化...
Attention-based Multi-level Feature Fusion for Named Entity Recognition | Request PDFwww.researchgate.net/publication/342793249_Attention-based_Multi-level_Feature_Fusion_for_Named_Entity_Recognition Abstract 命名实体识别是自然语言处理领域的一项基础性工作。近年来,表示学习方法(如字符嵌入和单词嵌入)取得了很好...
Multi-level feature fusion and multi-loss learning for person re-identificationSelf-attention moduleRelative weightMulti-loss learningWith the rise of deep learning technology, person re-identification (Re-id) technology has been developed rapidly. During the training process, many recent methods are ...
AlMahafzah, H, Imran, M & Sheshadri, HS 2012, `Multibiometric: Feature level fusion using FKP multi-instance biometric', International Journal of Computer Sciences, vol.9, no.3.AlMahafzah, H., Imran, M., Sheshadri, H.S.: Multibiometric: Feature Level Fusion Using FKP Multi-Instance ...
Inspired by the success of deep convolutional neural networks (CNNs) for many high-level vision tasks, in this paper, we propose a multi-scale feature fusion based neural network for underwater image enhancement. First, multi-scale features, including the local features and global features, are...
In this study, we propose a novel framework called attention-based multi-level feature fusion (AMFF), which is used to capture the multi-level features from different perspectives to improve NER. Our model consists of four components to respectively capture the local character-level, global ...
Power Quality Transient Disturbance Diagnosis Based on Dynamic Large Convolution Kernel and Multi-Level Feature Fusion Network First, the more fine-grained and more informative features of the transient signals are extracted by the dynamic large convolution kernel feature extraction ... C Zheng,Q Li,...
Therefore, we propose a new lightweight edge-guided multilevel feature fusion camouflaged object detection network, codenamed as LEMFNet. Initially, we adopt a lightweight CNN network model for feature extraction to reduce model complexity. Subsequently, we introduced a neighborhood feature association ...
(ML-FEM), multilevel feature fusion module (ML-FFM), neighborhood channel attention mechanism (N-CAM), multiscale feature pyramid module (MS-FPN), and feature association module (FA). First, we use the MS-Conv to extract different scale feature information in the object region. Second, the...
3.2.3. Multi-modal feature fusion ①利用串联操作和1×1卷积融合每一层级的颜色感知特性F_{i}和频率感知特性X_{i}。从三个层次的输出进行多层次特征分解,获得细粒度的伪迹线索,更好地进行伪造检测。 3.3. Multi-level feature disentanglement ①动机:两个挑战: (1)假伪影和真实特征纠缠在这些融合特征中。如...