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Found 4 papers, 0 papers with code
IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN
The proposed architecture exploits the concepts of edge and smoothing, multi-path dilated convolutional operations, channel squeezing, and boosting in CNN.
Small Object Detection using Deep Learning
The proposed system consists of a custom deep learning model Tiny YOLOv3, one of the flavors of very fast object detection model You Look Only Once (YOLO) is built and used for detection.
Malware Classification Using Deep Boosted Learning
In the hybrid learning, Deep features are extracted from customized CNN architectures and fed into the conventional machine learning classifier to improve the classification performance.
Deep Belief Networks Based Feature Generation and Regression for Predicting Wind Power
It is experimentally shown that the deep learning and unsupervised pre-training capabilities of DBN based model has comparable and in some cases better results than hybrid and complex learning techniques proposed for wind power prediction.
