Research and application of talent training evaluation model based on deep learning
The application of deep learning technology in target detection algorithm significantly improves the performance of the algorithm. Based on the traditional target detection algorithm, the task of target detection is summarized, including evaluation index, open data set, algorithm framework and the d...
Saved in:
| Main Author | |
|---|---|
| Format | Conference Proceeding |
| Language | English |
| Published |
SPIE
16.06.2023
|
| Online Access | Get full text |
| ISBN | 9781510666252 1510666257 |
| ISSN | 0277-786X |
| DOI | 10.1117/12.2682979 |
Cover
| Abstract | The application of deep learning technology in target detection algorithm significantly improves the performance of the algorithm. Based on the traditional target detection algorithm, the task of target detection is summarized, including evaluation index, open data set, algorithm framework and the defects of traditional algorithm. Therefore, taking the needs of object detection as the fulcrum, the training goal of research travel talents is clarified in this paper. There are two classification criteria: whether there is an explicit regional suggestion and whether a prior anchor frame is defined. The existing target detection algorithms are classified, and the evolutionary route of each algorithm is reviewed, and the mechanism, advantages, limitations and application scenarios of each method are summarized. The performance of representative target detection algorithms in open data sets is compared and analyzed. |
|---|---|
| AbstractList | The application of deep learning technology in target detection algorithm significantly improves the performance of the algorithm. Based on the traditional target detection algorithm, the task of target detection is summarized, including evaluation index, open data set, algorithm framework and the defects of traditional algorithm. Therefore, taking the needs of object detection as the fulcrum, the training goal of research travel talents is clarified in this paper. There are two classification criteria: whether there is an explicit regional suggestion and whether a prior anchor frame is defined. The existing target detection algorithms are classified, and the evolutionary route of each algorithm is reviewed, and the mechanism, advantages, limitations and application scenarios of each method are summarized. The performance of representative target detection algorithms in open data sets is compared and analyzed. |
| Author | Hong, Wang |
| Author_xml | – sequence: 1 givenname: Wang surname: Hong fullname: Hong, Wang organization: Ma'anshan Teachers College (China) |
| BookMark | eNotkFtLw0AUhBesYFv74i_YZyF1z26yl0cp3qAgeAHfwtmcU43ETchGf78t7dMwzPANzELMUp9YiCtQawBwN6DX2nodXDgTq-A8VKCstbrSMzFX2rnCeftxIRY5fyulfeXCXLy-cGYcmy-JiSQOQ9c2OLV9kv1OTthxmuQ0Ypva9Cn5D7vfY_rTE3cyYmaSe0vMg-z2oEPvUpzvsMu8OulSvN_fvW0ei-3zw9PmdltkUFUoLLIqma2PHsGDjYCm8aiCimUkbghpR1xSIKqMR1M1EQxRjEZ5a0syS3F95Oah5XoY-4aZ9vu5BlUfLqlB16dLzD8y4FaF |
| ContentType | Conference Proceeding |
| Copyright | COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. |
| Copyright_xml | – notice: COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. |
| DOI | 10.1117/12.2682979 |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| Editor | Patnaik, Srikanta |
| Editor_xml | – sequence: 1 givenname: Srikanta surname: Patnaik fullname: Patnaik, Srikanta organization: Indian Institute of Technology Bhubaneswar (India) |
| EndPage | 127030W-6 |
| ExternalDocumentID | 10_1117_12_2682979 |
| GroupedDBID | 29O 4.4 5SJ ACGFS ALMA_UNASSIGNED_HOLDINGS EBS F5P FQ0 R.2 RNS RSJ SPBNH UT2 |
| ID | FETCH-LOGICAL-s1059-6ae04ee68b8a1816b1a3c8a090b4bdecdadfde4d9dd538a35cb13ddbb308664d3 |
| ISBN | 9781510666252 1510666257 |
| ISSN | 0277-786X |
| IngestDate | Wed Jul 26 04:25:41 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-s1059-6ae04ee68b8a1816b1a3c8a090b4bdecdadfde4d9dd538a35cb13ddbb308664d3 |
| Notes | Conference Date: 2023-03-03|2023-03-05 Conference Location: Hong Kong, China |
| ParticipantIDs | spie_proceedings_10_1117_12_2682979 |
| PublicationCentury | 2000 |
| PublicationDate | 20230616 |
| PublicationDateYYYYMMDD | 2023-06-16 |
| PublicationDate_xml | – month: 6 year: 2023 text: 20230616 day: 16 |
| PublicationDecade | 2020 |
| PublicationYear | 2023 |
| Publisher | SPIE |
| Publisher_xml | – name: SPIE |
| SSID | ssj0028579 |
| Score | 2.2249963 |
| Snippet | The application of deep learning technology in target detection algorithm significantly improves the performance of the algorithm. Based on the traditional... |
| SourceID | spie |
| SourceType | Publisher |
| StartPage | 127030W |
| Title | Research and application of talent training evaluation model based on deep learning |
| URI | http://www.dx.doi.org/10.1117/12.2682979 |
| Volume | 12703 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1JS8QwFICDjhc9uYy4E9CbdOykadIexQUVRwSV8TYkeal4GcUZL_56X9q0qRuol9CG0u1r895L3kLInlQCFJNFlIEpIp5DHqlEYyPzVJsCclNm2x9cibM7fnGf3oeKn2V0yVT3zNu3cSX_oYp9yNVFyf6BbHNS7MBt5IstEsb2k_L7rZypveaqhKthJbpc91dOnDQVIFpZvaviN_tOfIFbKgBrn-viEQ8NZe-pO1S-z08MMFekIariFr07xflHYxFluzNWWNqeT3QruDIriwmGAZHJOGkNauV-PGzJSN8TiR8G4TKMn_WYcIG7eRA1jQNgZXrIUZ-N_EGzZFZKHJbmDo8HlzeNzZylVbrE-j5dbF79HNKn7Gqey6efxRMfhKs7F73nR9vSGm4XSTfEU9LrhuASmbHjZbLQSgW5Qm5qmBRh0hZM-lTQCiatYdIAk5YwaQmT4q6DSWuYXXJ3enJ7dBb5ghfRxKm5kVA25taKTGcKNS-h-yoxmYrzWHMN1oCCAiyHHADllEpSo_sJgNYJGqaCQ7JKOuOnsV0jFP81WWTcSMWAcxZrK5iNDWrf4GKd--tk172VUfh8J6OvUDZ-ddQmmQ_f3xbpTF9e7TaqalO943G-AyxONyk |
| linkProvider | EBSCOhost |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=Research+and+application+of+talent+training+evaluation+model+based+on+deep+learning&rft.au=Hong%2C+Wang&rft.date=2023-06-16&rft.pub=SPIE&rft.isbn=9781510666252&rft.issn=0277-786X&rft.volume=12703&rft.spage=127030W&rft.epage=127030W-6&rft_id=info:doi/10.1117%2F12.2682979&rft.externalDocID=10_1117_12_2682979 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0277-786X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0277-786X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0277-786X&client=summon |