Abstract: The present invention comprises: a storage unit (102) which stores a set of feature vectors, a set of quality labels, and a plurality of sets of non-quality labels; a non-quality label clustering unit (107) which calculates a clustering precision average for each of the plurality of sets of non-quality labels, said average being the average value of the clustering precision when the set of quality labels is used to perform clustering on subsets obtained by dividing the plurality of feature vectors by each of a plurality of elements that are respectively indicated by the plurality of non-quality labels, and by doing so, the non-quality label clustering unit (107) calculates a plurality of clustering precision averages that respectively correspond to the plurality of sets of non-quality labels; and a processing unit (108) which uses the clustering precision averages to generate a screen image capable of specifying at least one type of non-quality label that is adversely affecting the quality of a plurality of pieces of digital data.
| # | Name | Date |
|---|---|---|
| 1 | 202247012421.pdf | 2022-03-08 |
| 2 | 202247012421-STATEMENT OF UNDERTAKING (FORM 3) [08-03-2022(online)].pdf | 2022-03-08 |
| 3 | 202247012421-REQUEST FOR EXAMINATION (FORM-18) [08-03-2022(online)].pdf | 2022-03-08 |
| 4 | 202247012421-PROOF OF RIGHT [08-03-2022(online)].pdf | 2022-03-08 |
| 5 | 202247012421-POWER OF AUTHORITY [08-03-2022(online)].pdf | 2022-03-08 |
| 6 | 202247012421-NOTIFICATION OF INT. APPLN. NO. & FILING DATE (PCT-RO-105-PCT Pamphlet) [08-03-2022(online)].pdf | 2022-03-08 |
| 7 | 202247012421-FORM 18 [08-03-2022(online)].pdf | 2022-03-08 |
| 8 | 202247012421-FORM 1 [08-03-2022(online)].pdf | 2022-03-08 |
| 9 | 202247012421-DRAWINGS [08-03-2022(online)].pdf | 2022-03-08 |
| 10 | 202247012421-DECLARATION OF INVENTORSHIP (FORM 5) [08-03-2022(online)].pdf | 2022-03-08 |
| 11 | 202247012421-COMPLETE SPECIFICATION [08-03-2022(online)].pdf | 2022-03-08 |
| 12 | 202247012421-MARKED COPIES OF AMENDEMENTS [09-03-2022(online)].pdf | 2022-03-09 |
| 13 | 202247012421-FORM 13 [09-03-2022(online)].pdf | 2022-03-09 |
| 14 | 202247012421-AMMENDED DOCUMENTS [09-03-2022(online)].pdf | 2022-03-09 |
| 15 | 202247012421-FORM 3 [02-08-2022(online)].pdf | 2022-08-02 |
| 16 | 202247012421-FER.pdf | 2022-08-04 |
| 17 | 202247012421-FORM 3 [14-11-2022(online)].pdf | 2022-11-14 |
| 18 | 202247012421-FER_SER_REPLY [01-12-2022(online)].pdf | 2022-12-01 |
| 19 | 202247012421-FORM 3 [24-04-2023(online)].pdf | 2023-04-24 |
| 1 | deeplearninglowqualityE_03-08-2022.pdf |