论文信息 - Semantic feature representation and interpretation with context-free grammar and push-down automaton

Semantic feature representation and interpretation with context-free grammar and push-down automaton

Two key research issues are addressed: (i) A semantic representation and interpretation framework by using a lightweight self-supervised learning approach, namely the Context-Free Grammar and Push-Down Automaton; and (ii) A mobile phone App implementation of B-mode medical ultrasound imaging with a handheld probe, which can make use of the learned semantic features of scanned images for future home-based health screening.

Hock Soon Seah | Feng Lin | Ying Xu | Aurelio Jethro Prohara

[1] Yong Tsui Lee,et al. Semi-CNN architecture for effective spatio-temporal Learning in action recognition , 2020 .

[2] Li Cheng,et al. Transduction on Directed Graphs via Absorbing Random Walks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3] Zhongke Wu,et al. Voxelization and fabrication of freeform models , 2007 .

[4] F. Lin,et al. Imaging findings of fibrolamellar hepatocellular carcinomas on ultrasonography: A comparison with conventional hepatocellular carcinomas. , 2020, Clinical hemorheology and microcirculation.

[5] Feng Lin,et al. On-Site Volume Rendering with GPU-Enabled Devices , 2014, Wirel. Pers. Commun..

[6] Dilip K. Prasad,et al. Semi-CNN Architecture for Effective Spatio-Temporal Learning in Action Recognition , 2019, Applied Sciences.

[7] Feng Lin,et al. Cellular Image Classification , 2016 .

[8] Jun Yu,et al. Image classification by multimodal subspace learning , 2012, Pattern Recognit. Lett..

[9] Seah Hock Soon,et al. Evaluation of difference bounds for computing rational Bézier curves and surfaces , 2004, Comput. Graph..

[10] Sun-Yuan Kung,et al. Recent Collaborative R&D in Medical Imaging in Asia , 2020, J. Signal Process. Syst..

[11] Feng Lin,et al. A Graph-Theoretical Approach for Tracing Filamentary Structures in Neuronal and Retinal Images , 2016, IEEE Transactions on Medical Imaging.