… learn manual predictive regulation strategies from historical operating data, the paper
proposes a multi-task learning cascade network (LSTM multi-… Research progress of data-driven …

… -based measurement, image processing, and deep learning … , a dynamic multi-swarm
particle swarm optimization based on a … The proposed optimization algorithm can consider both …

… Existing target detection algorithms are oriented to obtain feature … based on inter-level cross
feature fusion. Method To detect … Our optimized detection is beneficial to further develop the …

… flame optimization (MFO) tracker based on dynamic adaptive … defines an adaptive multi-feature
fusion template and selects a … name feature, fused histogram of oriented gradient feature …

… of mainstream behavior detection algorithms in dangerous driving recognition. First, the …
normalization layer to optimize the network model. Then, an attitude detection algorithm is used …

… , a multi-layer feature fusion UAV aerial image detection algorithm based on YOLOv5 (you …
target sample size to optimize the expression ability of feature maps dynamically. Finally, in …

… in comparion with traditional signal processing algorithm. To further improve detection and
applicability of the network, feature fusion and spiking neural networks are proposed. Higher …

… been widely used in image processing, pattern recognition, signal processing fields. Driven
by big data, LDCT imaging algorithms based on deep learning have made great progress. …

… Motivated by the idea of reducing inter-modal differences … modality specific features and
optimizing feature fusion for … object detection,” IEEE Transactions on Image Processing, vol. …

… large computation but low recognition rate,a behavior recognition algorithm based on the
fusion of 3D convolutional neural network(3D-… Firstly,the 3D-CNN structure is optimized. Then,…