Predicting accuracy, total training time, and training time per epoch of the RCNN and CFF-RCNN on DB4 at different epochs, along with the statistical analyses results.

Figshare2022-01-20 更新30

Performance of the certification mark recognition model based on object detection developed using Google’s AutoML Vision.

标志识别

目标检测模型性能评估

Performance of the certification mark recognition model based on object detection developed using Google’s AutoML Vision.

NIAID Data Ecosystem10

Comparison of inference speed between YOLOv5s and ETSR-YOLO on the Jetson AGX Xavier platform.

目标检测模型性能评估

边缘计算平台部署

Comparison of inference speed between YOLOv5s and ETSR-YOLO on the Jetson AGX Xavier platform.

Figshare2023-12-14 更新30

Predicting accuracy, total training time, and training time per epoch of the RCNN and CFF-RCNN on DB4 at different epochs, along with the statistical analyses results.

目标检测模型性能评估

模型训练时间与准确率对比

Predicting accuracy, total training time, and training time per epoch of the RCNN and CFF-RCNN on DB4 at different epochs, along with the statistical analyses results.

NIAID Data Ecosystem20

Detection time and FPS of the FD_Net and other models.

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