WebThis paper proposes a DL-based intrusion detection system, DL-IDS, which uses the hybrid network of Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) to extract the temporal and spatial features of network traffic data to improve the accuracy of intrusion detection. WebApr 28, 2024 · To solve these problems, we propose an attention-based deep fusion CNN for smoke detection in the fog environment. First, a dataset of smoke detection in fog environment is established by online collection and offline shooting.
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WebSingle Image Dehazing Using Color Attenuation Prior. BMVC, Citeseer. [21]Zhu, Q., et al. (2015). "A fast single image haze removal algorithm using color attenuation prior." IEEE Transactions on Image Processing 24(11): 3522-3533. [22]Sun, C.-C., et al. (2016). Single image fog removal algorithm based on an improved dark channel prior method. WebApr 13, 2024 · In order to resolve the problem that the sample of image for internal detection of DN100 buried gas pipeline microleakage is single and difficult to identify, a recognition method of microleakage image of the pipeline internal detection robot is proposed. First, nongenerative data augmentation is used to expand the microleakage … homs news
Prediction and detection of freezing of gait in Parkinson’s disease ...
Web, An intrusion detection model based on feature reduction and convolutional neural networks, IEEE Access 7 (2024) 42210 – 42219. Google Scholar [17] Sun P., Liu P., Li … WebJan 1, 2024 · Request PDF Fog Computing and Deep CNN Based Efficient Approach to Early Forest Fire Detection with Unmanned Aerial Vehicles Fog computing assits the … WebMay 13, 2024 · Naseer et al. ( 2024) proposed a new intrusion detection system which applies the recent neural network-based classifiers, namely CNN, RNN and auto-encoders, for performing the training and testing processes using the bench mark wireless network dataset called NSL-KDD dataset. historically protected building