Search
| Leader | 00000nz a2200037n 45 0 | ||
|---|---|---|---|
| 001 | WKP|Q84270238 (VIAF cluster) (Authority/Source Record) | ||
| 003 | WKP | ||
| 005 | 20241221010739.0 | ||
| 008 | 241221nneanz||abbn n and d | ||
| 035 | ‡a (WKP)Q84270238 | ||
| 024 | ‡a 0000-0003-3294-3890 ‡2 orcid | ||
| 024 | ‡a 55981683900 ‡2 scopus | ||
| 035 | ‡a (OCoLC)Q84270238 | ||
| 100 | 0 | ‡a Antonio García-Manso ‡c researcher ‡9 en | |
| 375 | ‡a 1 ‡2 iso5218 | ||
| 400 | 0 | ‡a Antonio García-Manso ‡c investigador ‡9 es | |
| 400 | 0 | ‡a A García-Manso ‡c wetenschapper ‡9 nl | |
| 670 | ‡a Author's Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction | ||
| 670 | ‡a Author's Independent component analysis to detect clustered microcalcification breast cancers | ||
| 670 | ‡a Author's Low-Power and Low-Cost Environmental IoT Electronic Nose Using Initial Action Period Measurements | ||
| 670 | ‡a Author's Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques | ||
| 909 | ‡a (scopus) 55981683900 ‡9 1 | ||
| 909 | ‡a (orcid) 0000000332943890 ‡9 1 | ||
| 919 | ‡a precisepollengraindetectioninbrightfieldmicroscopyusingdeeplearningtechniques ‡A Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques ‡9 1 | ||
| 919 | ‡a lowpowerandlowcostenvironmentaliotelectronicnoseusinginitialactionperiodmeasurements ‡A Low-Power and Low-Cost Environmental IoT Electronic Nose Using Initial Action Period Measurements ‡9 1 | ||
| 919 | ‡a independentcomponentanalysistodetectclusteredmicrocalcificationbreastcancers ‡A Independent component analysis to detect clustered microcalcification breast cancers ‡9 1 | ||
| 919 | ‡a consistentperformancemeasurementofasystemtodetectmassesinmammogramsbasedonblindfeatureextraction ‡A Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction ‡9 1 | ||
| 946 | ‡a b ‡9 1 | ||
| 996 | ‡2 RERO|A020285453 | ||
| 996 | ‡2 ISNI|0000000070605233 | ||
| 996 | ‡2 ISNI|0000000068583127 | ||
| 996 | ‡2 PTBNP|1773705 | ||
| 996 | ‡2 PTBNP|1919703 | ||
| 996 | ‡2 J9U|987007274620605171 | ||
| 996 | ‡2 BNE|XX887385 | ||
| 996 | ‡2 DNB|1056326018 | ||
| 996 | ‡2 ISNI|0000000084440265 | ||
| 996 | ‡2 PTBNP|1192109 | ||
| 996 | ‡2 BNE|XX4697835 | ||
| 996 | ‡2 SUDOC|166222534 | ||
| 996 | ‡2 ISNI|0000000116799126 | ||
| 996 | ‡2 PTBNP|1689893 | ||
| 996 | ‡2 PTBNP|215355 | ||
| 996 | ‡2 BNE|XX1673210 | ||
| 996 | ‡2 LC|no2005118892 | ||
| 996 | ‡2 DNB|130031127 | ||
| 996 | ‡2 BIBSYS|11018573 | ||
| 996 | ‡2 DNB|116735317 | ||
| 996 | ‡2 BNC|981058522136006706 | ||
| 996 | ‡2 LC|n 2012056459 | ||
| 996 | ‡2 ISNI|0000000059430137 | ||
| 996 | ‡2 LC|n 85187141 | ||
| 997 | ‡a 0 0 lived 0 0 ‡9 1 |
