## 4 Conclusions
In Proceedings of the 22 nd ACM International Conference on Multimedia, Orlando, FL, USA, 3-7 November 2014. * [PERSON] _et al._ (2013) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Overfeat: Integrated recognition, localization and detection using convolutional networks. _arXiv_**2013**, arXiv:13126229. * [PERSON] _et al._ (2018) [PERSON]; [PERSON]; [PERSON] [PERSON] Real time object detection and tracking using Deep Learning and OpenCV. In Proceedings of the 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 11-12 July 2018. * [PERSON] _et al._ (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Deepcut: Object segmentation from bounding box annotations using convolutional neural networks. _IEEE Trans. Med. Imaging_**2016**, _36_, 674-683. [CrossRef] [PubMed]
* [PERSON] _et al._ (2015) [PERSON]; [PERSON] [PERSON]; [PERSON] Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA, 7-12 June 2015. * [PERSON] _et al._ (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] 3D U-Net: Learning dense volumetric segmentation from sparse annotation. In _International Conference on Medical Image Computing and Computer-Assisted Intervention_; Springer: Berlin/Heidelberg, Germany, 2016. * _[PERSON] et al. (2016)_ [PERSON]; [PERSON]; [PERSON] V-net: Fully convolutional neural networks for volumetric medical image segmentation. In Proceedings of the 2016 Fourth International Conference on 3D Vision (3 DV), Stanford, CA, USA, 25-28 October 2016. * _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] H-DenseUNet: Hybrid densely connected UNet for liver and tumor segmentation from CT volumes. _IEEE Trans. Med. Imaging_**2018**, _37_, 2663-2674. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Unet++: A nested u-net architecture for medical image segmentation. In _Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support_; Springer. Berlin/Heidelberg, Germany, 2018; pp. 3-11. * _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mdu-net: Multi-scale densely connected u-net for biomedical image segmentation. _arXiv_**2018**, arXiv:181200352. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] DUNet: A deformable network for retinal vessel segmentation. _Knowl.-Based Syst._**2019**, _178_, 149-162. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans. _Front. Bioeng. Biotechnol._**2020**, \(8\), 1471. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON] Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities. In _International MICCAI Brainlesion Workshop_; Springer. Berlin/Heidelberg, Germany, 2018. * _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Stacked dense u-nets with dual transformers for robust face alignment. _arXiv_**2018**, arXiv:181201936. * _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] nnu-net: Self-adapting framework for u-net-based medical image segmentation. _arXiv_**2018**, arXiv:180910486. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Acute and sub-acute stroke lesion segmentation from multimodal MRI. _Comput. Meth. Prog. Biol._**2020**, _194_, 105521. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON] [PERSON] IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet. In _International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging_; Springer: Berlin/Heidelberg, Germany, 2018.