MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02307nab|a22003017a|4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
62837 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240919021229.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
201030s2018||||xxu|||p|op||||00||0|eng|d |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
https://arxiv.org/abs/1805.11784v1 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MX-TxCIM |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Wen-Xuan Liao |
| 9 (RLIN) |
16876 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Hyperspectral imaging technology and transfer learning utilized in identification haploid maize seeds |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
USA : |
| Name of publisher, distributor, etc. |
Cornell University, |
| Date of publication, distribution, etc. |
2018. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
It is extremely important to correctly identify the cultivars of maize seeds in the breeding process of maize. In this paper, the transfer learning as a method of deep learning is adopted to establish a model by combining with the hyperspectral imaging technology. The haploid seeds can be recognized from large amount of diploid maize ones with great accuracy through the model. First, the information of maize seeds on each wave band is collected using the hyperspectral imaging technology, and then the recognition model is built on VGG-19 network, which is pre-trained by large-scale computer vision database (Image-Net). The correct identification rate of model utilizing seed spectral images containing 256 wave bands (862.5-1704.2nm) reaches 96.32%, and the correct identification rate of the model utilizing the seed spectral images containing single-band reaches 95.75%. The experimental results show that, CNN model which is pre-trained by visible light image database can be applied to the near-infrared hyperspectral imaging-based identification of maize seeds, and high accurate identification rate can be achieved. Meanwhile, when there is small amount of data samples, it can still realize high recognition by using transfer learning. The model not only meets the requirements of breeding recognition, but also greatly reduce the cost occurred in sample collection. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Imagery |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
10231 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
11127 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Haploidy |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1925 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Plant breeding |
| Miscellaneous information |
AGROVOC |
| Source of heading or term |
|
| 9 (RLIN) |
1203 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Maize |
| Miscellaneous information |
AGROVOC |
| Source of heading or term |
|
| 9 (RLIN) |
1173 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
16877 |
| Personal name |
Xuan-Yu Wang |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
16776 |
| Personal name |
Dong An |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
16777 |
| Personal name |
Yaoguang Wei |
| 773 0# - HOST ITEM ENTRY |
|---|
| Place, publisher, and date of publication |
USA : Cornell University, 2018. |
| Title |
ArXiv |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Article |
| Suppress in OPAC |
No |
| Source of classification or shelving scheme |
Dewey Decimal Classification |