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Full-Text Articles in Engineering
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Journal of System Simulation
Abstract: Abstruct: A lot of research achievements have been made in image dehazing based on neural network,but there aiming at the fog residue, even the color distortion and texture loss, in complex outdoor image dehazing, an image dehazing network based on densely connected residual block and channel pixel attention is proposed. Densely connected residual blocks are used to extract and fuse the features of foggy images,and the repair module with channel pixel attention mechanism is used to repair the color and texture of the feature maps. The experimental results show that, compared with the existing methods, the proposed method and …
Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng
Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng
Journal of System Simulation
Abstract: Aircraft engine remaining useful life (RUL) prediction is the core issue in equipmentfailure prognostics and health management (PHM). Aiming at the characteristics of high dimensionality, high lag and complexity of engine data, a multi-scale attention-based bidirectional long short-term memory neural network model based on self-training weights is proposed. Multi-scale features are extracted through bidirectional long short-term memory neural network (BiLSTM) of different scales. A fusion algorithm based on self-training weights is proposed, and an attention mechanism is introduced to screen features at different scales to improve prediction accuracy. Various models are compared on the NASA's C-MAPSS data set. The …
Vehicle Detection Method Based On Multi Scale Feature Fusion, Yin Wang, Feixiang Wang, Qianlai Sun
Vehicle Detection Method Based On Multi Scale Feature Fusion, Yin Wang, Feixiang Wang, Qianlai Sun
Journal of System Simulation
Abstract: Vehicle detection is the important research content and hotspot in the intelligent transportation. Aiming at the low detection accuracy and poor small-scale recognition effect of the traditional vehicle detection algorithm, an improved detection method based on YOLOv4(you only look once v4) is proposed to improve the detection performance of small target vehicles in traffic scenes. By redesigning the YOLOv4 network, the MobileNetv2 deep separable convolution module is used to replace the traditional convolution, and the convolutional block attention module (CBAM) attention module is integrated into the feature extraction network to ensure the detection accuracy of the model and reduce …