Laser & Optoelectronics Progress, Volume. 60, Issue 6, 0610005(2023)
Application of a Lightweight Convolutional Neural Network in Ship Classification
[1] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).
[2] Li X M, Chen H, Qi X J et al. H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes[J]. IEEE Transactions on Medical Imaging, 37, 2663-2674(2018).
[3] Zhang X Y, Zou J H, He K M et al. Accelerating very deep convolutional networks for classification and detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 1943-1955(2016).
[4] Zhang D, Wang H T, Jiang Y et al. Research on real-time face recognition algorithm based on lightweight network[J]. Journal of Frontiers of Computer Science and Technology, 14, 317-324(2020).
[5] Sun W B, Wang R, Sun L Z et al. Cross-age face recognition based on deep learning[J]. Laser & Optoelectronics Progress, 59, 0215001(2022).
[7] Liu J X, Ban W, Chen Y et al. Multi-dimensional CNN fused algorithm for hyperspectral remote sensing image classification[J]. Chinese Journal of Lasers, 48, 1610003(2021).
[8] Wang W X, Fu Y T, Dong F et al. Infrared ship target detection method based on deep convolution neural network[J]. Acta Optica Sinica, 38, 0712006(2018).
[9] Hou X H, Jin G D, Tan L N. Survey of ship detection in SAR images based on deep learning[J]. Laser & Optoelectronics Progress, 58, 0400005(2021).
[10] Wang Y N, Sun X S, Yu L X. Lightweight synthetic aperture radar ship detection algorithm with enhanced receptive field[J]. Acta Optica Sinica, 51, 0210008(2022).
[11] Bi Z B, Zhang S Y, Yang H et al. Survey of ship detection in video surveillance based on shallow machine learning[J]. Journal of System Simulation, 33, 2792-2807(2021).
[12] Chen W. Research on ship moving position tracking based on video processing technology[J]. Ship Science and Technology, 41, 40-42(2019).
[13] Wang A L, Liu M H, Xue D et al. Hyperspectral image classification combined dynamic convolution with triplet attention mechanism[J]. Laser & Optoelectronics Progress, 59, 1015011(2022).
[14] Ren Y M, Yang J, Guo Z Q et al. Ship classification method for point cloud images based on three dimensional convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 161022(2020).
[15] Chen X W. Research on ship classification technology based on deep learning[J]. Ship Science and Technology, 41, 142-144(2019).
[16] Szegedy C, Vanhoucke V, Ioffe S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).
[17] Szegedy C, Ioffe S, Vanhoucke V et al. Inception-v4, inception-ResNet and the impact of residual connections on learning[C], 4278-4284(2017).
[18] Tan M X, Le Q V. Efficientnet: Rethinking model scaling for convolutional neural networks[C], 6105-6114(2019).
[20] Sandler M, Howard A, Zhu M L et al. MobileNetV2: inverted residuals and linear bottlenecks[C], 4510-4520(2018).
[21] Xiao Z J, Yang X D, Wei X et al. Improved lightweight network in image recognition[J]. Journal of Frontiers of Computer Science and Technology, 15, 743-753(2021).
[22] Wang G R, Wang K Z, Lin L. Adaptively connected neural networks[C], 1781-1790(2019).
[23] Han K, Wang Y H, Tian Q et al. GhostNet: more features from cheap operations[C], 1577-1586(2020).
[24] Howard A, Sandler M, Chen B et al. Searching for MobileNetV3[C], 1314-1324(2019).
[26] Chen Y, Li J, Xiao H et al. Dual path net-works[C], 4470-4478(2017).
[27] Radosavovic I, Kosaraju R P, Girshick R et al. Designing network design spaces[C], 10425-10433(2020).
Get Citation
Copy Citation Text
Wenliang Wang, Xiaodi Yang, Boya Zhang, Jishun Ma, Peng Zeng, Peng Han. Application of a Lightweight Convolutional Neural Network in Ship Classification[J]. Laser & Optoelectronics Progress, 2023, 60(6): 0610005
Category: Image Processing
Received: Nov. 23, 2021
Accepted: Jan. 17, 2022
Published Online: Mar. 7, 2023
The Author Email: Yang Xiaodi (1755018902@qq.com)