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Project Code: TCMAPY1434
Project Title:OPTIMIZED TRAFFIC FLOW DETECTION WITH YOLOV9 AND BYTETRACKView DetailsProject Code: TCMAFS1283
Project Title:Dementia Classification using deep learning approachesView DetailsProject Code: TCMAPY1443
Project Title:Leaf-Guard A Deep Learning Framework for Early Detection of Plant PathogensView DetailsProject Code: TCMAPY1420
Project Title:AI Driven Diagnosis of Oral Malignancies through machine learning and deep learningView DetailsProject Code: TCMAPY1418
Project Title:Revolutionizing Neurodegenerative Disease Treatment with Deep Learning ModelsView DetailsProject Code: TCMAPY1408
Project Title:Image Centric Indoor Navigation Solution for Visually Impaired PeopleView DetailsProject Code: TCMAPY1407
Project Title:MACHINE LEARNING APPROACH FOR INTELLIGENT TRAFFIC MANAGEMENTView DetailsProject Code: TCMAPY1400
Project Title:Disaster Management and Mapping Using Satellite ImagesView Details S.no | Project Code | Project Name | Action |
|---|---|---|---|
| 1 | TCMAPY1434 | OPTIMIZED TRAFFIC FLOW DETECTION WITH YOLOV9 AND BYTETRACK | |
| 2 | TCMAFS1283 | Dementia Classification using deep learning approaches | |
| 3 | TCMAPY1443 | Leaf-Guard A Deep Learning Framework for Early Detection of Plant Path... | |
| 4 | TCMAPY1442 | Train Track Crack Classification | |
| 5 | TCMAPY1424 | Unauthorised Access Personal Devices | |
| 6 | TCMAPY1420 | AI Driven Diagnosis of Oral Malignancies through machine learning and ... | |
| 7 | TCMAPY1418 | Revolutionizing Neurodegenerative Disease Treatment with Deep Learning... | |
| 8 | TCMAPY1408 | Image Centric Indoor Navigation Solution for Visually Impaired People | |
| 9 | TCMAPY1407 | MACHINE LEARNING APPROACH FOR INTELLIGENT TRAFFIC MANAGEMENT | |
| 10 | TCMAPY1400 | Disaster Management and Mapping Using Satellite Images |
Project Code: TCMAPY1434
Project Title:OPTIMIZED TRAFFIC FLOW DETECTION WITH YOLOV9 AND BYTETRACKView DetailsProject Code: TCMAFS1283
Project Title:Dementia Classification using deep learning approachesView DetailsProject Code: TCMAPY1443
Project Title:Leaf-Guard A Deep Learning Framework for Early Detection of Plant PathogensView DetailsProject Code: TCMAPY1420
Project Title:AI Driven Diagnosis of Oral Malignancies through machine learning and deep learningView DetailsProject Code: TCMAPY1418
Project Title:Revolutionizing Neurodegenerative Disease Treatment with Deep Learning ModelsView DetailsProject Code: TCMAPY1408
Project Title:Image Centric Indoor Navigation Solution for Visually Impaired PeopleView DetailsProject Code: TCMAPY1407
Project Title:MACHINE LEARNING APPROACH FOR INTELLIGENT TRAFFIC MANAGEMENTView DetailsProject Code: TCMAPY1400
Project Title:Disaster Management and Mapping Using Satellite ImagesView Details S.no | Project Code | Project Name | Action |
|---|---|---|---|
| 1 | TCMAPY1434 | OPTIMIZED TRAFFIC FLOW DETECTION WITH YOLOV9 AND BYTETRACK | |
| 2 | TCMAFS1283 | Dementia Classification using deep learning approaches | |
| 3 | TCMAPY1443 | Leaf-Guard A Deep Learning Framework for Early Detection of Plant Path... | |
| 4 | TCMAPY1442 | Train Track Crack Classification | |
| 5 | TCMAPY1424 | Unauthorised Access Personal Devices | |
| 6 | TCMAPY1420 | AI Driven Diagnosis of Oral Malignancies through machine learning and ... | |
| 7 | TCMAPY1418 | Revolutionizing Neurodegenerative Disease Treatment with Deep Learning... | |
| 8 | TCMAPY1408 | Image Centric Indoor Navigation Solution for Visually Impaired People | |
| 9 | TCMAPY1407 | MACHINE LEARNING APPROACH FOR INTELLIGENT TRAFFIC MANAGEMENT | |
| 10 | TCMAPY1400 | Disaster Management and Mapping Using Satellite Images |
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Takeoff Edu Group's deep learning projects cover a wide range of topics, including computer vision, natural language processing, and generative models. Each project comes with comprehensive instructions, and our team is available 24/7 to offer support and guidance along the way.
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
