AI SearchDurian ripeness prediction using audio processing and deep learning (Record no. 31864)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03548nas a2200421 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818094231.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240229s2022 th u m tt 000 a eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12421728 |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.DSAI-22-10 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Sarach Rujiranurak |
| 245 10 - TITLE STATEMENT | |
| Title | Durian ripeness prediction using audio processing and deep learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 43 leaves : |
| Other physical details | ill. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. DSAI-22-10 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Data Science and Artificial Intelligence, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Sc.) - Asian Institute of Technology, 2022 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Due to its taste and odor, durian is a high-value fruit product in Thailand. With their custard-like pulps, durians can be eaten at various ripeness stages, giving a variety of sweetness appreciated by consumers. However, determining the level of ripeness of a durian is complicated. The fruit is covered with hard spikes and a thick peel, making it challenging to observe its condition from the outside. In practice, experts knock a durian with a rubber stick and listen to the sound that is typical to distinguish ripe and unripe fruit. This technique requires a great deal of experience on the part of the listener to make accurate predictions. This study indicated the audio processing and deep learning techniques applied for durian ripeness detection from the knocking sound. The audio samples were recorded from 611 Mon-thong durians harvested from the south region of Thailand, Chumphon, Surat Thani, and Yala provinces. There were four classes of ripeness levels, unripe, mid-ripe, ripe, and overripe, for the target of the deep learning models. The sound from each hit was extracted and transformed into three forms of spectrograms, Short Time Fourier Transform (STFT), mel spectrogram, and Mel Frequency Cepstral Coefficients (MFCCs). Two deep learning models, ResNet50 and Audio Spectrogram Transformer (AST), were evaluated for their performance when trained with different data structures and learning procedures. This study found that ResNet-50 provided the best prediction at 74.5% accuracy when predicting in four levels and 89.4% accuracy when predicting two classes when grouping the targets into unripe and ripe conditions. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer sound processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Neural networks (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Deep learning (Machine learning) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Durian |
| Geographic subdivision | Thailand |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dailey, Matthew N., |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chaklam Silpasuwanchai, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Loc, Thai Nguyen, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | The Royal Thai Government, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. DSAI-22-10 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B20423">http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B20423</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b12421728 |
| b | mnait |
| c | a |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 250307 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 240314 |
| First date, FD (RLIN) | m |
| -- | a |
| -- | a |
| -- | 0 |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 67-Electronic Resource |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 40-Archives |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2024-02-29 |
| RECORD Id | RECORD # : i13487930 |
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| Barcode | Barcode : 30050120899009 |
| CREATED | CREATED : 2025-07-03 |
| RECORD Id | RECORD # : i13537209 |
| LPATRON | LPATRON : 0 |
| LCHKIN | LCHKIN : - |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Price effective from | Koha item type | Barcode | Copy number |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.DSAI-22-10 | 18/08/2026 | 18/08/2026 | 67-Electronic Resource | ||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.DSAI-22-10 | 18/08/2026 | 18/08/2026 | 40-Archives | 30050120899009 | 1 |