分离
发表于 2025-3-27 00:04:59
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归功于
发表于 2025-3-27 04:17:31
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洞穴
发表于 2025-3-27 08:19:52
4.2 Effective Interdisciplinary Teamserent settings has shown that only classes.dex files of apks are sufficient for Android malware detection. The proposed deep learning framework with convolutional neural networks could achieve 97.76% accuracy in detecting Android malware with minimal information requirement.
CHECK
发表于 2025-3-27 12:38:59
Malware Family Classification Model Using Convolutional Neural Network,s proposed. Malware family recognition is formulated as a multi-classification task, and an accurate solution is obtained by training convolutional neural network with images of malware executable files. Ten families of malware have been considered here for building the models. The image dataset wit
bypass
发表于 2025-3-27 15:02:23
Malware and Benign Detection Using Convolutional Neural Network,input. The convolutional neural networks-based classification model proves accuracy of 93% in discriminate from malware and benign files. The convolutional neural network-based malware detection model has higher performance when compared with deep neural network classification model trained with GIS
不在灌木丛中
发表于 2025-3-27 19:13:26
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LATE
发表于 2025-3-28 00:13:56
Plant Health Report Through Advanced Convolution Neural Network Methodology,ble of identifying the disease with higher efficiency and is able to suggest the measures that farmers can take to avoid the pest infection and diseases that have been identified in their plants, to grow a healthy plant for high yield. The disease detection is done using the classifier present in th
vector
发表于 2025-3-28 05:53:39
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defeatist
发表于 2025-3-28 07:58:09
Pediatric Skeletal Age Assessment Using Deep Learning Proceedings,oal is to leverage deep learning visualization techniques for better interpretation of our results. Overall, our proposed model achieved a competitive MAE of 7.61 months on the test set provided by Radiological Society of North America (RSNA).
critic
发表于 2025-3-28 10:40:11
A Novel Model for Disease Identification in Mango Plant Leaves Using Multimodal Conventional and Te of the diseases using conventional methods is time consuming, and there can be over usage of chemicals to overcome the diseases. The technological methods along with conventional methods can be used to identify the diseases efficiently and treat the disease time and cost effectively. This paper giv