Mobile QR Code QR CODE

※ The user interface design of www.ieiespc.org has been recently revised and updated. Please contact inter@theieie.org for any inquiries regarding paper submission.

Journal Search

  1. Home
  2. Archive
  3. 2022-02 (Vol.11 No.01)
  4. 10.5573/IEIESPC.2021.11.1.34
XML PDF INFO REF

REFERENCES

1 
He Kaiming, et al. , 2016, Deep residual learning for image recognition., Proceedings of the IEEE conference on computer vision and pattern recognitionDOI
2 
Sandler Mark, et al. , 2018, Mobilenetv2: Inverted residuals and linear bottlenecks., Proceedings of the IEEE conference on computer vision and pattern recognitionDOI
3 
Liu Wei, et al. , 2016, Ssd: Single shot multibox detector., European conference on computer vision. Springer, ChamDOI
4 
Lin Tsung-Yi, et al. , 2017, Feature pyramid networks for object detection., Proceedings of the IEEE conference on computer vision and pattern recognitionDOI
5 
Choi Jun Ho, et al. , 2020, Multi-scale Non-local Feature Enhancement Network for Robust Small-object Detection., IEIE Transactions on Smart Processing & Computing, Vol. 9, No. 4, pp. 274-283DOI
6 
Ronneberger Olaf , Philipp Fischer , Thomas Brox , 2015, U-net: Convolutional networks for biomedical image segmentation., International Conference on Medical image computing and computer-assisted intervention. Springer, ChamDOI
7 
Long , Jonathan , Evan Shelhamer , Trevor Darrell. , 2015, Fully convolutional networks for semantic segmentation., Proceedings of the IEEE conference on computer vision and pattern recognitionDOI
8 
Tan Mingxing, Ruoming Pang, Quoc V. Le., 2020, Efficientdet: Scalable and efficient object detection., Proceedings of the IEEE/CVF conference on computer vision and pattern recognitionDOI
9 
Uzkent, Burak , Christopher Yeh , Stefano Ermon , 2020, Efficient object detection in large images using deep reinforcement learning., Proceedings of the IEEE/CVF Winter Conference on Applications of Computer VisionDOI
10 
Quang, Tran Ngoc , Seunghyun Lee , Byung Cheol Song. , 2021, Object Detection Using Improved Bi-Directional Feature Pyramid Network., Electronics, Vol. 10, No. 6, pp. 746DOI
11 
Kim Donggeun, et al. , 2020, Real-time Robust Object Detection Using an Adjacent Feature Fusion-based Single Shot Multibox Detector., IEIE Transactions on Smart Processing & Computing, Vol. 9, No. 1, pp. 22-27DOI
12 
Chen Guobin, et al. , 2017, Learning efficient object detection models with knowledge distillation., Advances in neural information processing systemsURL
13 
Shih, Kuan-Hung , Ching-Te Chiu , Yen-Yu Pu. , 2019, Real-time object detection via pruning and a concatenated multi-feature assisted region proposal network., ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEEDOI
14 
Everingham Mark, et al. , 2015 , The pascal visual object classes challenge: A retrospective., International journal of computer vision, Vol. 111, No. 1, pp. 98-136DOI
15 
Lin Tsung-Yi, et al. , 2014, Microsoft coco: Common objects in context., European conference on computer vision. Springer, ChamDOI
16 
Geiger, Andreas , Philip Lenz , Raquel Urtasun. , 2012, Are we ready for autonomous driving? the kitti vision benchmark suite., 2012 IEEE conference on computer vision and pattern recognition. IEEEDOI
17 
Ren Shaoqing, et al. , 2015, Faster r-cnn: Towards real-time object detection with region proposal networks., Advances in neural information processing systems, Vol. 28, pp. 91-99URL
18 
He Kaiming, et al. , 2017, Mask r-cnn., Proceedings of the IEEE international conference on computer visionDOI
19 
Pang Yanwei, et al. , 2019, Efficient featurized image pyramid network for single shot detector., Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern RecognitionDOI
20 
Grill Jean-Bastien, et al. , 2020, Bootstrap Your Own Latent: A new approach to self-supervised learning., Neural Information Processing SystemsURL
21 
Li Chunyuan, et al. , 2021, Efficient Self-supervised Vision Transformers for Representation Learning., arXiv preprint arXiv:2106.09785DOI
22 
Zagoruyko, Sergey , Nikos Komodakis , 2016, Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer., arXiv preprint arXiv:1612.03928DOI
23 
Kim, Jangho , SeongUk Park , Nojun Kwak. , 2018, Paraphrasing complex network: network compression via factor transfer., Proceedings of the 32nd International Conference on Neural Information Processing SystemsDOI
24 
Tung, Frederick , Greg Mori. , 2019, Similarity-preserving knowledge distillation., Proceedings of the IEEE/CVF International Conference on Computer VisionDOI
25 
Chen Defang, et al. , 2021., Cross-layer distillation with semantic calibration., Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35, No. 8URL
26 
Paszke Adam, et al. , 2019, Pytorch: An imperative style, high-performance deep learning library., Advances in neural information processing systems, Vol. 32, pp. 8026-8037URL
27 
Mirzadeh, Seyed Iman , et al. , 2020, Improved knowledge distillation via teacher assistant., Proceedings of the AAAI Conference on Artificial Intelligence., Vol. 34, No. 04DOI
28 
Yalniz, I. Zeki , et al. , 2019, Billion-scale semi-supervised learning for image classification., arXiv preprint arXiv:1905.00546DOI