MAIM 发表于 2025-3-26 23:17:28
Classification of Malware Variant Based on Ensemble Learning,learning model. First, malware binary data was transformed into a gray-scale image and the GIST texture feature of the image was extracted. Then, KNN (K Nearest Neighbor) and RF (random forest) method are used as base learners and a malware variant classification model was proposed based on the voti游行 发表于 2025-3-27 03:12:59
http://reply.papertrans.cn/63/6207/620602/620602_32.png有危险 发表于 2025-3-27 08:36:17
Spatio-Temporal Graph Convolutional Networks for DDoS Attack Detecting,ernet. Many DDoS detection algorithms based on machine learning technology have emerged in recent years, for example, the LUCID algorithm, GNN model. But considering that DDoS attacks are based on both time and space, these algorithms only considered time and ignored space. Besides, by piece networkesoteric 发表于 2025-3-27 13:16:16
Cerebral Microbleeds Detection Based on 3D Convolutional Neural Network,n of the location and amount of CMBs in brain tissue is crucial for the diagnosis, prevention and treatment of related diseases, where traditional Convolutional Neural Network (CNN) has been applied but may fail to achieve high enough detection accuracy. To alleviate this issue, we utilize 3D FullyObsessed 发表于 2025-3-27 15:14:40
Liver Tumor Segmentation of CT Image by Using Deep Fully Convolutional Network,f popular method. However, the performance of the traditional convolutional network is limited by the network depth. To improve the accuracy of liver tumor segmentation, we propose a cascaded deep fully convolutional network (DFCN) which uses ResNet as the basis network followed by side output layer昏暗 发表于 2025-3-27 19:20:05
http://reply.papertrans.cn/63/6207/620602/620602_36.pngColonoscopy 发表于 2025-3-27 23:57:27
http://reply.papertrans.cn/63/6207/620602/620602_37.pngcrumble 发表于 2025-3-28 05:22:48
http://reply.papertrans.cn/63/6207/620602/620602_38.png考博 发表于 2025-3-28 08:05:34
http://reply.papertrans.cn/63/6207/620602/620602_39.pngOutwit 发表于 2025-3-28 14:06:00
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