The proposed method achieves an average mean precision (mAP) of 87.24% and reduces inference time by 15%, demonstrating significant improvements in both accuracy and efficiency compared to the baseline. Overall,
YOLOv7-tinier makes several key improvements to the YOLOv7-tiny model. First, it uses partial convolution to reconstruct the feature extraction module ELAN in the backbone network, reducing the number of parameters and extracting more diverse and hierarchical features and thus improving the detection...
Since then, various groups have tackled YOLO to make improvements. Some examples of these new versions include the powerfulYOLOv5andYOLOR. Each of these iterations attempted to improve upon past incarnations, and YOLOv7 is now the highest-performing model of the family with its release. How doe...
Facial identity is a way of recognizing a person’s identity by using his facial features. Facial identity recognition has always been a demanding area in the domain of computer vision. Although, it has several challenges due to the varying complexities of the facial attributes, however, in rece...
Since then, various groups have tackled YOLO to make improvements. Some examples of these new versions include the powerfulYOLOv5andYOLOR. Each of these iterations attempted to improve upon past incarnations, and YOLOv7 is now the highest-performing model of the family with its release. ...
To address the challenge of balancing model size, detection speed, and accuracy in transmission line inspections, this study adopts YOLOv716 as the base network for relevant improvements. We propose a detection algorithm named YOLOv7-CWFD, which balances lightweight design and high performance. Com...
This can result in the loss of target features and ultimately affect recognition accuracy. To address the issue at hand, we propose the addition of dynamic ODConv to the original yolov7 model. This will help tackle the problems of error and omission detection wuring complex background ...
In Sect. 2, we introduce the railway turnout and the problem of identifying the states of the sliding chairs. In Sect. 3, an overview of the proposed method is first presented. Then, we elaborate on the data preprocessing procedure and the detailed improvements in YOLOv7 to identify the ...
The parameter-free attention mechanism SimAM is incorporated into both the neck network and the prediction output section, enhancing the ability of the model to extract essential features of strip surface defects and improving detection accuracy. The experimental results on the NEU-DET dataset show ...
A vehicle detection algorithm based on the improved YOLOv7-tiny algorithm suitable for deploying on edge terminal devices is proposed to better protect people s lives and property. A deep powerful residual ( DP_Res) convolutional block isconstructed to perform the lightweight improvements on the ...