[1] |
杨国亮, 洪志阳, 许楠 . 基于多尺度编码-解码网络的皮肤病变图像分割[J]. 中国医学物理学杂志, 2019,36(2): 199-204.
|
|
YANG G L , HONG Z Y , XU N . Segmentation of skin lesion image based on multi-scale encoder-decoder network[J]. Chinese Journal of Medical Physics, 2019,36(2): 199-204.
|
[2] |
杨国亮, 洪志阳, 王志元 ,等. 基于改进全卷积网络的皮肤病变图像分割[J]. 计算机工程与设计, 2018,39(11): 3500-3505.
|
|
YANG G L , HONG Z Y , WANG Z Y ,et al. Image segmentation of skin lesions based on improved fully convolution network[J]. Computer Engineering and Design, 2018,39(11): 3500-3505.
|
[3] |
何雪英, 韩忠义, 魏本征 . 基于深度卷积神经网络的色素性皮肤病识别分类[J]. 计算机应用, 2018,38(11): 3236-3240.
|
|
HE X Y , HAN Z Y , WEI B Z . Pigmented skin lesion recognition and classification based on deep convolutional neural network[J]. Journal of Computer Applications, 2018,38(11): 3236-3240.
|
[4] |
LONG J , SHELHAMER E , DARREL T . Fully convolutional networks for semantic segmentation[C]// The IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2015: 3431-3440.
|
[5] |
RONNEBERGER O , FISCHER P , BROX T ,et al. U-Net:convolutional networks for biomedical image segmentation[J]. Medical Image Computing and Computer Assisted Intervention, 2015: 234-241.
|
[6] |
IGLOVIKOV V , SHEVETS A . TernausNet:U-Net with VGG11 encoder pre-trained on ImageNet for image segmentation[J]. arXiv preprint, 2018,arXiv:1801.05746.
|
[7] |
CHAURASIA A , CULURCIELLO E . LinkNet:exploiting encoder representations for efficient semantic segmentation[C]// 2017 IEEE Visual Communications and Image Processing (VCIP). Piscataway:IEEE Press, 2017: 1-4.
|
[8] |
JAHANIFAR M , TAJEDDIN N Z , KOOHBANANI N A ,et al. Segmentation of skin lesions and their attributes using multi-scale convolutional neural networks and domain specific augmentations[J]. arXiv preprint, 2018,arXiv:1809.10243.
|
[9] |
AL-MASNI M A , AL-ANTARI M A , CHOI M ,et al. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks[J]. Computer Methods and Programs in Biomedicine, 2018,162: 221-231.
|
[10] |
WANG X H , JIANG X D , DING H H ,et al. Bi-directional dermoscopic feature learning and multi-scale consistent decision fusion for skin lesion segmentation[J]. IEEE Transactions on Image Processing, 2019,29: 3039-3051.
|
[11] |
XIE F Y , YANG J W , LIU J ,et al. Skin lesion segmentation using high-resolution convolutional neural network[J]. Computer Methods and Programs in Biomedicine, 2020,186: 105241.
|
[12] |
YU L , CHEN H , DOU Q ,et al. Automated melanoma recognition in dermoscopy images via very deep residual networks[J]. IEEE Transactions on Medical Imaging, 2017,36(4): 994-1004.
|
[13] |
NAVARRO F , ESCUDERO-VI?OLO M , BESCóS J . Accurate segmentation and registration of skin lesion images to evaluate lesion change[J]. IEEE Journal of Biomedical and Health Informatics, 2019,23(2): 501-508.
|
[14] |
KUREK M , JA?KOWSKI W , . Heterogeneous team deep Q-learning in low-dimensional multi-agent environments[C]// The 2016 IEEE Conference on Computational Intelligence and Games (CIG). Piscataway:IEEE Press, 2016: 1-8.
|
[15] |
ZHANG H G , JIANG H , LUO Y H ,et al. Data-driven optimal consensus control for discrete-time multi-agent systems with unknown dynamics using reinforcement learning method[J]. IEEE Transactions on Industrial Electronics, 2017,64(5): 4091-4100
|
[16] |
LEI B Y , XIA Z M , JIANG F ,et al. Skin lesion segmentation via generative adversarial networks with dual discriminators[J]. IEEE Transactions on Industrial Electronics, 2020,64.
|
[17] |
HAWAS A R , GUO Y H , DU C L ,et al. OCE-NGC:a neutrosophic graph cut algorithm using optimized clustering estimation algorithm for dermoscopic skin lesion segmentation[J]. Applied Soft Computing Journal, 2020,86: 105931.
|
[18] |
MU C , ZHAO Q , SUN C ,et al. A novel Q-learning algorithm for optimal tracking control of linear discrete-time systems with unknown dynamics[J]. Applied Soft Computing, 2019,82: 1-13.
|
[19] |
ARULKUMARAN K , DEISENROTH M P , BRUNDAGE M ,et al. Deep reinforcement learning:a brief survey[J]. IEEE Signal Processing Magazine, 2017,34(6): 26-38.
|
[20] |
FOERSTER J N , CHEN R Y , AL-SHEDIVAT M ,et al. Learning with opponent-learning awareness[C]// The 17th International Conference on Autonomous Agents and Multiagent Systems. New York:ACM Press, 2018: 122-130.
|
[21] |
ZHENG Y , MENG Z P , HAO J Y ,et al. Weighted double deep multiagent reinforcement learning in stochastic cooperative environments[C]// The 15th Pacific Rim International Conference on Artificial Intelligence. New York:ACM Press, 2018: 421-429.
|
[22] |
ZHANG K Q , YANG Z R , LIU H ,et al. Fully decentralized multi-agent reinforcement learning with networked agents[C]// The 35th International Conference on Machine Learning. New York:ACM Press, 2018: 5872-5881.
|