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1 wrz 2021 · DFL-Net can better distinguish background and objects while avoiding misclassification. The results show that DFL-Net achieves a superior mAP of 83.1%, which outperforms most compared SSD-like detectors and three two-stage detectors, including Faster R-CNN and R-FCN.
In this paper, we propose a new object detection approach that improves existing one-stage anchor-based methods via a Distinguishable Feature Learning Network (DFL-Net). DFL-Net integrates distinguishable features into the learning process to improve the accuracy of object detection.
1 wrz 2021 · In this paper, we propose a new object detection approach that improves existing one-stage anchor-based methods via a Distinguishable Feature Learning Network (DFL-Net).
Network (DFL-Net). DFL-Net integrates distinguishable features into the learn-ing process to improve the accuracy of object detection. Notably, we implement DFL-Netbyafull-scalefusionmoduleandanattention-guidedmodule.Inthefull-scalefusionmodule,wefirstlearnthedistinguishablefeaturesateachscale(layer)
the reasons that the DFL is stepping up talks regard-ing the regulatory framework in European football. The DFL’s recent proposal for an absolute cap on team costs is one example of possible action that could be taken. Our position is clear: It is necessary to establish regulations that protect leagues and
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20 paź 2003 · How to Read the Logs. Although the exact format of each log entry depends on how yoursyslog recipient works, most are very much alike. The way in whichlogs are read is also dependent on how your syslog recipient works.Syslog daemons on UNIX servers usually log to text files, line byline.
