Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networ...Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity limit.Despite the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for SC.In this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are summarized.Next,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are summarized.Applications of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are summarized.Finally,some challenges and future research directions are presented to provide guidance for further research of SC.展开更多
On the internet,image tampering has become awidespread issue,leading to a series of adverse effects on the trustworthiness of image information.In response to this challenge,this paper proposes an image tampering loca...On the internet,image tampering has become awidespread issue,leading to a series of adverse effects on the trustworthiness of image information.In response to this challenge,this paper proposes an image tampering localization method based on dual-stream feature fusion.Our approach employs a dualstream encoder to simultaneously extract features from both the RGB stream and the noise stream,enabling the localization of forged regions.By introducing an attention mechanism,these two feature streams are fused,further enhancing the detection performance.Additionally,the Atrous Spatial Pyramid Pooling(ASPP)module is integrated to expand the receptive field and extract contextual information at different scales.Finally,the decoder generates a tamper region localization map.Experimental results demonstrate that the proposed method exhibits significant performance improvements on three widely used datasets,affirming its effectiveness in the field of image tampering detection.展开更多
基金supported by the Natural Science Foundation of China under Grants 61971084,62025105,62001073,62272075the National Natural Science Foundation of Chongqing under Grants cstc2021ycjh-bgzxm0039,cstc2021jcyj-msxmX0031+1 种基金the Science and Technology Research Program for Chongqing Municipal Education Commission KJZD-M202200601the Support Program for Overseas Students to Return to China for Entrepreneurship and Innovation under Grants cx2021003,cx2021053.
文摘Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity limit.Despite the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for SC.In this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are summarized.Next,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are summarized.Applications of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are summarized.Finally,some challenges and future research directions are presented to provide guidance for further research of SC.
文摘On the internet,image tampering has become awidespread issue,leading to a series of adverse effects on the trustworthiness of image information.In response to this challenge,this paper proposes an image tampering localization method based on dual-stream feature fusion.Our approach employs a dualstream encoder to simultaneously extract features from both the RGB stream and the noise stream,enabling the localization of forged regions.By introducing an attention mechanism,these two feature streams are fused,further enhancing the detection performance.Additionally,the Atrous Spatial Pyramid Pooling(ASPP)module is integrated to expand the receptive field and extract contextual information at different scales.Finally,the decoder generates a tamper region localization map.Experimental results demonstrate that the proposed method exhibits significant performance improvements on three widely used datasets,affirming its effectiveness in the field of image tampering detection.
