| Type of Material: | Thesis |
| Title: | Diagnosis Of Diabetes By Tongue Analysis Using Image Processing |
| Researcher: | Srividhya, E |
| Guide: | Muthukumaravel, A |
| Department: | Department of Engineering and Technology(Computer Science and Engineering) |
| Publisher: | Bharath University, Chennai |
| Place: | Chennai |
| Year: | 2022 |
| Language: | English |
| Subject: | Computer Science | Computer Science Artificial Intelligence | Engineering and Technology | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2022 |
| Fulltext: | Shodhganga |
| 000 | 00000ctm a2200000ua 4500 | |
| 001 | 455072 | |
| 003 | IN-AhILN | |
| 005 | 2024-09-23 11:39:06 | |
| 008 | __ | 240923t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_455072 |
| 040 | __ | |aBHAU_600073|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aSrividhya, E|eResearcher |
| 110 | __ | |aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein|0U-0446 |
| 245 | __ | |aDiagnosis Of Diabetes By Tongue Analysis Using Image Processing |
| 260 | __ | |aChennai|bBharath University, Chennai|c2022 |
| 300 | __ | |dDVD |
| 502 | __ | |bPhD|cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai|d2022 |
| 520 | __ | |aThe tongue is a major part of the human body to taste, speak and swallow food. The tongue portion is directly connected with our internal organ. If any problem happens in the internal organ, it reflects the effect through the tongue. The tongue center portion is connected with the stomach, pancreas. Side portions are connected with the liver. The tongue tip is connected with the heart, etc. In this research work, an efficient Decision Support System is used to detect diabetes based on the Characterization of tongue images using three soft computing methods. The proposed methods are namely Multiclass Support Vector Machine (MSVM), Sequential Learning Neural Network (SLNN) and Convolutional Neural Network with Long short time memory (CNN-LSTM) architecture. The binary classifier uses the hyper-plane, which is also called the decision boundary between two classes called a Multi-Class Support Vector Machine (MSVM). The SVM method determines the hyper plane in dividing two classes. The boundary is maximized be |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aComputer Science Artificial Intelligence |
| 653 | __ | |aEngineering and Technology |
| 700 | __ | |aMuthukumaravel, A|eGuide |
| 856 | __ | |yShodhganga|uhttp://shodhganga.inflibnet.ac.in/handle/10603/380215 |
| 905 | __ | |afromsg |
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