YOLOv5’s overall architecture diagram. Full size image Baseline network architecture YOLOv5 is a single-stage object detection algorithm based on anchors, and it is designed to provide a high-performance, high-speed, and high-accuracy framework for object detection. YOLOv5 has many versions, incl...
To en- hance performance of CNNs, recent researches have mainly investigated three important factors of networks: depth, width, and cardinality. From the LeNet architecture [4] to Residual-style Networks [5,6,7,8] so far, the network has become deeper for rich representation. VGGNet [9] ...
From the LeNet architecture [4] to Residual-style Networks [5,6,7,8] so far, the network has become deeper for rich representation. VGGNet [9] shows that stacking blocks with the same shape gives fair results. Following the same spirit, ResNet [5] stacks the same topology of residual...
of Human-Made Structures in Urban Areas for Assessment of Risk and VulnerabilityAdvanced Research Based on Multi-Dimensional Point Cloud AnalysisAdvancements in Geospatial Planning and Assessment of Green Infrastructure in Cities of the FutureAdvances and Innovations in Land Use/Cover MappingAdvances in ...
Figure 1 represents the block diagram of the proposed BSBE-PPODLC approach. Figure 1. Block diagram of BSBE-PPODLC system. 2.1. Encryption Using the BSBE Technique The BSBE technique is employed in this study for secure encryption of the RSIs. In the BSBE technique, a user may want ...
The VGG19 model is identical to the VGG16 model with the exception that it supports 19 layers. The “16” and “19” represent the model’s number of weight layers. This indicates that VGG-19 has three more ConvL, compared to VGG-16. ResNet architecture is a kind of ANN that allows...
Figure 2. Framework diagram of the microexpression recognition method based on the ADP-DSTN feature fusion and Convolutional Block Attention Module. (1) In response to the challenge of achieving a low detection accuracy for subtle features present in microexpression facial action units, this paper...
For example, SAB enhances the accuracy of DenseNet201, ResNet34, ResNet50, and VGG16 by 0.5%, 0.8%, 1.2%, and 2%, respectively. When the SA block is incorporated into the networks, we observe a comparable pattern in the AUC scores. Specifically, the performance of Xe increased by 5%,...
The structure diagram is shown in Figure 5. The importance of each neuron is different, and the assigned weights should be unique. Among them, the neurons with higher importance show significant spatial inhibition effects. The linear difference between other neurons and the target neuron is derived...
A detailed block diagram of the EMB is shown in Figure 2. The main contributions of this study are as follows: Figure 1. Overall architecture of the single-shot multibox detector with the enhanced map block (SSD-EMB). The input of the EMB is a feature map produced from convolutional ...