An intelligent control plan for the secondary cooling of continuous casting of slab was put forward. An off-line simulation of the system by using neural networks combined with fuzzy logic control is provided. The res...An intelligent control plan for the secondary cooling of continuous casting of slab was put forward. An off-line simulation of the system by using neural networks combined with fuzzy logic control is provided. The results show that the intelligent control system can not only control the surface temperature of the bloom of the secondary cooling but also has a good ability of self-adaptation and self-learning.展开更多
Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.H...Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.展开更多
To progressively provide the competitive rate-distortion performance for aerial imagery,a quantized block compressive sensing(QBCS) framework is presented,which incorporates two measurement-side control parameters:mea...To progressively provide the competitive rate-distortion performance for aerial imagery,a quantized block compressive sensing(QBCS) framework is presented,which incorporates two measurement-side control parameters:measurement subrate(S) and quantization depth(D).By learning how different parameter combinations may affect the quality-bitrate characteristics of aerial images,two parameter allocation models are derived between a bitrate budget and its appropriate parameters.Based on the corresponding allocation models,a model-guided image coding method is proposed to pre-determine the appropriate(S,D) combination for acquiring an aerial image via QBCS.The data-driven experimental results show that the proposed method can achieve near-optimal quality-bitrate performance under the QBCS framework.展开更多
文摘An intelligent control plan for the secondary cooling of continuous casting of slab was put forward. An off-line simulation of the system by using neural networks combined with fuzzy logic control is provided. The results show that the intelligent control system can not only control the surface temperature of the bloom of the secondary cooling but also has a good ability of self-adaptation and self-learning.
文摘Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.
基金supported by the Natural Science Foundation of Shanghai(18ZR1400300)
文摘To progressively provide the competitive rate-distortion performance for aerial imagery,a quantized block compressive sensing(QBCS) framework is presented,which incorporates two measurement-side control parameters:measurement subrate(S) and quantization depth(D).By learning how different parameter combinations may affect the quality-bitrate characteristics of aerial images,two parameter allocation models are derived between a bitrate budget and its appropriate parameters.Based on the corresponding allocation models,a model-guided image coding method is proposed to pre-determine the appropriate(S,D) combination for acquiring an aerial image via QBCS.The data-driven experimental results show that the proposed method can achieve near-optimal quality-bitrate performance under the QBCS framework.
