购买
下载掌阅APP,畅读海量书库
立即打开
畅读海量书库
扫码下载掌阅APP

参考文献

[1]FELZENSZWALB P,MCALLESTER D,RAMANAN D.A discriminatively trained,multiscale,deformable part model[C]//Institute of Electrical and Electronics Engineers,2008 IEEE Conference on Computer Vision and Pattern Recognition,Anchorage,AK,USA,2008.New Jersey:IEEE,2008:1-8.

[2]FAN X N,SHI P F,NI J J,et al.A thermal infrared and visible images fusion based approach for multitarget detection under complex environment[J].Math.Problems Eng.,2015,2015:1774-1778.

[3]RAGHAVENDRA R,DORIZZI B,RAO A,et al.Particle swarm optimization based fusion of near infrared and visible images for improved face verification[J].Pattern Recognit.,2011,44(2):401-411.

[4]ULUSOY I,YURUK H.New method for the fusion of complementary information from infrared and visual images for object detection[J].IET Image Process.,2011,5(1):36-48.

[5]WANG Y C,XIAO Y,LU J Y,et al.Discriminative multi-view dynamic image fusion for cross-view 3-d action recognition[J].IEEE Trans.Neural Netw.Learn.Syst.,2022,33(10):5332-5345.

[6]CHEN J,LI X J,LUO L B,et al.Infrared and visible image fusion based on target-enhanced multiscale transform decomposition[J].Information Sciences,2020,508:64-78.

[7]ZHANG Q,LIU Y,HAN J G,et al.Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images:a review[J].Information Fusion,2018,40:57-75.

[8]谭博彦.遥感图像目标识别文献综述[J].电脑知识与技术,2016(12X):206-208.

[9]YU L,LIU S P,WANG Z F.A general framework for image fusion based on multi-scale transform and sparse representation[J].Information Fusion,2015,24:147-164.

[10]张文国,李向东,刘存超.基于稀疏表示的SAR/红外图像彩色融合[J].舰船电子工程,2016,36(3):4.

[11]ZHAO W D,LU H M,DONG W.Multisensor image fusion and enhancement in spectral total variation domain[J].IEEE Transactions on Multimedia,2018,20(4):866-879.

[12]LI H,WU X J,KITTLER J.MDLatLRR:a novel decomposition method for infrared and visible image fusion[J].IEEE Transactions on Image Processing,2020,29:4733-4746.

[13]晁锐,张科,李言俊.一种基于小波变换的图像融合算法[J].电子学报,2004,32(5):750-753.

[14]杨桄,童涛,陆松岩,等.基于多特征的红外与可见光图像融合[J].光学精密工程,2014,22(2):8.

[15]ZHANG Y,LIU Y,SUN P,et al.IFCNN:a general image fusion framework based on convolutional neural network[J].Information Fusion,2020,54:99-118.

[16]王洪斌,肖嵩,曲家慧,等.基于多分支CNN的高光谱与全色影像融合处理[J].光学学报,2021,41(7):9.

[17]MA J Y,TANG L F,Fan F,et al.SwinFusion:cross-domain long-range learning for general image fusion via swin transformer[J].IEEE/CAA Journal of Automatica Sinica,2022,9(7):1200-1217.

[18]LIU Z,LIN Y T,CAO Y T,et al.Swin transformer:hierarchical vision transformer using shifted windows[C]//Institute of Electrical and Electronics Engineers,2021 IEEE/CVF International Conference on Computer Vision,Montreal,QC,Canada.New Jersey:IEEE,2021:9992-10002.

[19]XU H,WANG X Y,MA J Y.DRF:disentangled representation for visible and infrared image fusion[J].IEEE Transactions on Instrumentation and Measurement,2021,99:1-13.

[20]LIU J Y,FAN X Y,HUANG Z B,et al.Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection[C]//Institute of Electrical and Electronics Engineers,2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition,New Orleans,LA,USA.New Jersey:IEEE,2022:5792-5801.

[21]ZHAO W D,XIE S G,ZHAO F,et al.MetaFusion:infrared and visible image fusion via meta-feature embedding from object detection[C]//Institute of Electrical and Electronics Engineers,2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).New Jersey:IEEE,2023:13955-13965.

[22]ZHAO F,ZHAO W D,YAO L B,et al.Self-supervised feature adaption for infrared and visible image fusion[J].Information Fusion,2021,76:189-203.

[23]ZHAO F,ZHAO W D.Learning specific and general realm feature representations for image fusion[J].IEEE Transactions on Multimedia (TMM),2020,23:2745-2756.

[24]ZHAO F,ZHAO W D,LU H C.Interactive feature embedding for infrared and fisible image fusion[J].IEEE Transactions on Neural Networks and Learning Systems[Early access],2023.

[25]MA J Y,YU W,LIANG P W,et al.FusionGAN:a generative adversarial network for infrared and visible image fusion[J].Inf.Fusion,2019,48:11-26.

[26]MA J Y,XU H,JIANG J J,et al.DDcGAN:a dual-discriminator conditional generative adversarial network for multi-resolution image fusion[J].IEEE Trans.Image Process.,2020,29:4980-4995.

[27]MA J Y,LIANG P W,YU W,et al.Infrared and visible image fusion via detail preserving adversarial learning[J].Inf.Fusion,2020,54:85-98.

[28]陈华,陈书海,张平,等.K-means算法在遥感分类中的应用[J].红外与激光工程,2000(02):26-30.

[29]王志刚,朱振海,王红梅,等.光谱角度填图方法及其在岩性识别中的应用[J].遥感学报,1999,3(1):60-65.

[30]刘伟强,陈鸿,夏德深.基于马尔可夫随机场的快速图像分割[J].中国图象图形学报:A辑,2001,6(3):228-233.

[31]RUMELHART D E,HINTON G E,WILLIAMS R J.Learning representations by back-propagating errors[J].nature,1986,323(6088):533-536.

[32]KRIZHEVSKY A,SUTSKEVER I,HINTON G.ImageNet classification with deep convolutional neural networks[J].Communications of the ACM,2017,60(6):84-90.

[33]HE K M,ZHANG X Y,REN S Q,et al.Deep residual learning for image recognition[C]//Institute of Electrical and Electronics Engineers,Proceedings of the IEEE conference on computer vision and pattern recognition.New Jersey:IEEE,2016:770-778.

[34]CUI Z T,GUO W W,ZHANG Z H,et al.Ellipse-FCN:oil tanks detection from remote sensing images with fully convolution network[C]//Institute of Electrical and Electronics Engineers,IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium.New Jersey:IEEE,2020:2855-2858.

[35]FANG W Z,SUN Y Y,JI R,et al.Recognizing global dams from high-resolution remotely sensed images using convolutional neural networks[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021,14:6363-6371.

[36]LI L,WANG C,ZHANG H,et al.SAR image ship object generation and classification with improved residual conditional generative adversarial network[J].IEEE Geoscience and Remote Sensing Letters,2020,19:1-5.

[37]MA W P,SHEN J C,ZHU H,et al.A novel adaptive hybrid fusion network for multiresolution remote sensing images classification[J].IEEE Transactions on Geoscience and Remote Sensing,2021(99):1-17.

[38]LI X B,JIANG B T,WANG S J,et al.A human-computer fusion framework for aircraft recognition in remote sensing images[J].IEEE Geoscience and Remote Sensing Letters,2019(99):1-5.

[39]HAN Y Q,YANG X Y,PU T,et al.Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images[J].IEEE Transactions on Geoscience and Remote Sensing,2021,60:1-18.

[40]LI J R,TIAN J W,GAO P,et al.Ship detection and fine-grained recognition in large-format remote sensing images based on convolutional neural network[C]//Institute of Electrical and Electronics Engineers,IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium.New Jersey:IEEE,2020:2859-2862.

[41]LIU Y S,LIU Y B,DING L W.Scene classification based on two-stage deep feature fusion[J].IEEE Geoscience and Remote Sensing Letters,2017,15(2):183-186.

[42]JIA Y Q,SHELHAMER E,DONAHUE J,et al.Caffe:convolutional architecture for fast feature embedding[C]//Association for computing Machinery,Institute of Electrical and Electronics Engineers,Proceedings of the 22nd ACM international conference on Multimedia.New York:ACM,2014:675-678.

[43]ZHAO W D,TONG T T,WANG H P,et al.Diversity consistency learning for remote-sensing object recognition with limited labels[J].IEEE Transactions on Geoscience and Remote Sensing (TGRS),2022,60:1-11.

[44]ZHAO W D,LV X Z,WANG H P,et al.Weakly correlated distillation for remote sensing object recognition[J].IEEE Transactions on Geoscience and Remote Sensing,2023.

[45]ZHAO W D,LIU J N,LIU Y,et al.Teaching teachers first and then student:hierarchical distillation to improve long-tailed object recognition in aerial images[J].IEEE Transactions on Geoscience and Remote Sensing (TGRS),2022,60:1-12.

[46]ZHAO W D,YANG R K,LIU Y,et al.Style-content metric learning for multidomain remote sensing object recognition[C]//Association for the Advancement of Artificial Intelligence 2023 AAAI Conference on Artificial Intelligence.Menlo Park:AAAI Press,2023:3624-3632. 87fWKEd4OWhTkNmLekdU0KSQaMgDi6nrMunP1LSuBrCzOq/K8pYRN6y8dHBa3ZWM

点击中间区域
呼出菜单
上一章
目录
下一章
×