| Ref.No: | 61514800 |
| Start date: | 22.07.2022 |
| End date: | 21.06.2025 |
| Approval date: | 15.07.2022 |
| Department: | ELECTRICAL & COMPUTER ENGINEERING |
| Sector: | COMPUTER SCIENCE |
| Financier: | 3Η ΠΡΟΚΗΡΥΞΗ ΕΛΙΔΕΚ Υ.Δ., ELIDEK |
| Budget: | 31.500,00 € |
| Public key: | 9ΣΖ246ΨΖΣ4-ΖΔΜ |
| Scientific Responsible: | Prof. STEFANOS KOLLIAS |
| Email: | stefanos@cs.ntua.gr |
| Description: | THE SUBJECT OF THE THESIS (PROJECT) IS TRANSPARENT AND EXPLAINABLE DEEP LEARNING AND ARTIFICIAL INTELLIGENCE. DEEP LEARNING SYSTEMS IN MOST CASES ARE VERY COMPLICATED AND IT IS DIFFICULT TO BE INTERPRETED. CONSEQUENTLY, IN THE VAST MAJORITY OF USE CASES |
