Micro Organism Image Recognition and Disease Prediction Based on DL
| dc.contributor.author | Aakash.B 1NH20IS002 Saran.B.V.N 1NH20IS028 Vishnu.C 1NH20IS033 Abhi.K 1NH20IS067 | |
| dc.date.accessioned | 2024-11-13T09:05:14Z | |
| dc.date.available | 2024-11-13T09:05:14Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenges faced by human-operated microscopy, deep-learning-based methods have been proposed for microscopic image analysis of a wide range of microorganisms, including viruses, bacteria, fungi, and parasites. We believe that deep-learning technology-based systems will be on the front line of monitoring and investigation of microorganisms. Hence, here we are proposing a model that which can classify and detects the type of organism using the CNN based transfer learning algorithm of deep learning. Once after the detection of the organism, the spread of diseases are also predicted from the detected output. | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/16303 | |
| dc.language.iso | en | |
| dc.publisher | NHCE | |
| dc.title | Micro Organism Image Recognition and Disease Prediction Based on DL | |
| dc.type | Other |