Ahmad Farooq
ABSTRACT
In Chinese medicine, the patient's body constitution plays a crucial role in determining the course of treatment because it is so intrinsically linked to the patient's physiological and pathological processes. Traditional Chinese medicine practitioners use tongue diagnosis to determine a person's constitutional type during an examination. An effective solution is needed to overcome the complexity of this setting before the tongue image constitution recognition system can be deployed on a non-invasive mobile device for fast, efficient, and accurate constitution recognition. We will use deep deterministic policy gradients to implement tongue retrieval techniques. We suggested a new method for image retrieval systems based on Deep Deterministic Policy Gradients (DDPG) in an effort to boost the precision of database searches for query images. We present a strategy for enhancing image retrieval accuracy that uses the complexity of individual instances to split the dataset into two subsets for independent classification using Deep reinforcement learning. Experiments on tongue datasets are performed to gauge the efficacy of our suggested approach; in these experiments, deep reinforcement learning techniques are applied to develop a retrieval system for pictures of tongues affected by various disorders. Using our proposed strategy, it may be possible to enhance image retrieval accuracy through enhanced recognition of tongue diseases. Databases containing pictures of tongues affected by a wide range of disorders will be used as examples. The experimental results suggest that the new approach to computing the main colour histogram outperforms the prior one. Though the difference is tiny statistically, the enhanced retrieval impact is clear to the human eye. The tongue is similarly brought to the fore to emphasise the importance of the required verbal statement. Both investigations used tongue images classified into five distinct categories.
- Heneghan, C., Flynn, J., O'Keefe, M., & Cahill, M. (2002). Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis. Medical Image Analysis, 6(4), 407–429. https://doi.org/10.1016/S1361-8415(02)00058-0Google Scholar
Cross Ref
- Huang, F., Cheng, Y., Jin, C., Zhang, Y., & Zhang, T. (2017). Deep Multimodal Embedding Model for Fine-grained Sketch-based Image Retrieval. SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 929–932. https://doi.org/10.1145/3077136.3080681Google ScholarDigital Library
- Jin, Y., Liu, Q., Shen, L., & Zhu, L. (2021). Deep deterministic policy gradient algorithm based on convolutional block attention for autonomous driving. Symmetry, 13(6). https://doi.org/10.3390/sym13061061Google Scholar
- Matsui, Y., Ito, K., Aramaki, Y., Fujimoto, A., Ogawa, T., Yamasaki, T., & Aizawa, K. (2017). Sketch-based manga retrieval using manga109 dataset. Multimedia Tools and Applications, 76(20), 21811–21838. https://doi.org/10.1007/s11042-016-4020-zGoogle ScholarDigital Library
- Retrieval, F. I., & Dilemma, S. I. (2017). Edinburgh Research Explorer Fine-Grained Image Retrieval: the Text / Sketch Input Dilemma Fine-Grained Image Retrieval: the Text / Sketch Input Dilemma. Bmvc.Google Scholar
- Ruiter, N. V., Müller, T. O., Stotzka, R., Gemmeke, H., Reichenbach, J. R., & Kaiser, W. A. (2002). Automatic image matching for breast cancer diagnostics by a 3D deformation model of the mamma. Biomedizinische Technik. Biomedical Engineering, 47 Suppl 1, 644–647. https://doi.org/10.1515/bmte.2002.47.s1b.644Google ScholarCross Ref
- Song, J., Song, Y., Xiang, T., Science, C., Mary, Q., Kingdom, U., Hospedales, T., & Ruan, X. (n.d.). Deep Multi-task Attribute-driven Ranking for Fine-grained Sketch-based Image Retrieval. 1–11.Google Scholar
- Su, B., Lu, S., & Tan, C. L. (2011). Blurred image region detection and classification. MM’11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops, June 2014, 1397–1400. https://doi.org/10.1145/2072298.2072024Google ScholarDigital Library
- Wu, D., Dong, X., Shen, J., & Hoi, S. C. H. (2020). Reducing Estimation Bias via Triplet-Average Deep Deterministic Policy Gradient. IEEE Transactions on Neural Networks and Learning Systems, 31(11), 4933–4945. https://doi.org/10.1109/TNNLS.2019.2959129Google ScholarCross Ref
- Yan, S., Yu, L., & Xie, Y. (2021). Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 8092–8101. https://doi.org/10.1109/CVPR46437.2021.00800Google ScholarCross Ref
- Yuan, X., Ren, L., Lu, J., & Zhou, J. (2018). Relaxation-Free Deep Hashing via Policy Gradient. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11208 LNCS, 141–157. https://doi.org/10.1007/978-3-030-01225-0_9Google ScholarDigital Library
- Zhang, Q., Lu, J., & Jin, Y. (2021). Artificial intelligence in recommender systems. Complex & Intelligent Systems, 7(1), 439–457. https://doi.org/10.1007/s40747-020-00212-wGoogle ScholarCross Ref
- Zhang, X., Wang, H., Zhang, Y., Gao, X., Wang, G., & Zhang, C. (2021). Improved fuzzy clustering for image segmentation based on a low-rank prior. Computational Visual Media, 7(4), 513–528. https://doi.org/10.1007/s41095-021-0239-3Google ScholarCross Ref
Recommendations
Machine Learning Based Tongue Image Recognition for Diabetes Diagnosis
Machine Learning for Cyber SecurityAbstractTongue diagnosis of Traditional Chinese Medicine (TCM) is of great significance in the diagnosis of diabetes. To reduce the subjectivity of doctors in clinical diagnosis, this paper proposes a method for diabetic tongue image recognition based on ...
Can you 'read' tongue movements? Evaluation of the contribution of tongue display to speech understanding
Lip reading relies on visible articulators to ease speech understanding. However, lips and face alone provide very incomplete phonetic information: the tongue, that is generally not entirely seen, carries an important part of the articulatory ...
Learning-based tongue detection for automatic tongue color diagnosis system
AbstractTongue diagnosis is expected to be used for preventive medicine, because it can check the health condition comprehensively. For the computer-assisted tongue diagnosis, automatic tongue detection from the facial pictures is needed. In this study, ...
Comments