Depthwise Separable Convolution Depthwise Separable Convolution于2017年在《MobileNets: Efficient Convolutional Neural Networks for Mobile VisionApplications》提出。 标准卷积操作所使用卷积核与输入特征具有相同的通道数,卷积核个数即为输出特征的通道数。 ... ...
Depth-wise separable convolutiondetectioninceptionFriedman testCLASSIFICATIONNETWORKSPedestrian detection is one of the most challenging research areas in computer vision. Compared to traditional hand-crafted methods, convolutional neural networks (CNNs) have superior detection results. The single-stage detection...
We propose SpeakerNet - a new neural architecture for speaker recognition and speaker verification tasks. It is composed of residual blocks with 1D depth-wise separable convolutions, batch-normalization, and ReLU layers. This architecture uses x-vector based statistics pooling layer to map variable-...
We propose a new real-time detection algorithm for MIS tools, which called depth-wise separable convolutional network with convolutional long short-term ... Y Liu,Z Zhao,P Shi,... - 《IEEE Transactions on Medical Robotics & Bionics》 被引量: 0发表: 2022年 Lightweight Driver Behavior Identif...
A Novel Depth-Wise Separable Convolutional Model for Remote Sensing Scene Classificationdoi:10.1007/s12524-024-01904-3Deep LearningNeural networkArtificial IntelligenceClassificationRemote sensing imageWith the advancement in satellite and Artificial Intelligence (AI), the increase in observation of the earth...
A new tool wear prediction method based on multidomain feature fusion by attention-based depth-wise separable convolutional neural network is proposed to solve these problems. In this method, multidomain features of cutting force and vibration signals are extracted and recombined into feature tensors....
Depth-wise separable convolutionsInfectious lung diseases are a global health concern, and deep learning, particularly convolutional neural networks (CNNs), holds promise for diagnosing these conditions using chest x-rays (CXRs). However, existing models prioritize accuracy, often neglecting challenges ...
Then, these features were transferred to the Depth-wise Squeeze and Excitation Block. The proposed DSEB based on the combination of Squeeze-Excitation and Depth-wise Separable Convolution enabled to reveal of critical information by weighting the features with a lightweight gating mechanism for ...
Then, these features were transferred to the Depth-wise Squeeze and Excitation Block. The proposed DSEB based on the combination of Squeeze-Excitation and Depth-wise Separable Convolution enabled to reveal of critical information by weighting the features with a lightweight gating mechanism for ...
These optimal features are then incorporated into the Multiscale Depth-wise Separable Adaptive Temporal Convolutional Network (MDS-ATCN) for the ambient Air Quality Prediction (AQP) process. The variables within MDS-ATCN are further refined using the proposed FEO-PFA to enhance predictive accuracy. ...