AI SearchA multi-modal framework for context-aware plant disease classification and segmentation integrating visual and textual features (Record no. 835)
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| fixed length control field | 03552nam a2200373 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260817161322.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260218s20259999th mm 000 eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12476699 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.DSAI-25-05 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Doula, Md Shafi Ud |
| 245 10 - TITLE STATEMENT | |
| Title | A multi-modal framework for context-aware plant disease classification and segmentation integrating visual and textual features |
| 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. | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 74 leaves : |
| Other physical details | ill.+ |
| Accompanying material | 1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. DSAI-25-05 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Eng.) - Asian Institute of Technology, 2025 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Plant diseases substantially challenge agricultural productivity and global food security. Hence, better intelligent and interpretable diagnostic frameworks are needed. An auto mated disease identification system can reduce the human effort in checking large farms, and early detection and identification will minimize the loss, which ultimately positively affects the economy. Traditional image-based deep learning models, particularly Convo lutional Neural Networks (CNNs), often struggle to distinguish visually similar diseases due to the absence of contextual information. To address these limitations, we present an innovative multi-modal deep learning framework that effectively combines visual and textual data to improve plant disease classification and segmentation. Initially, the framework incorporates a linguistically enriched Text Encoder, where disease-related descriptions are preprocessed using natural language processing (NLP) techniques to extract salient noun, numerical, adjective, and adverbial features. These refined textual representations are then encoded using a fine-tuned transformer-based language model, capturing domain-specific semantics crucial for disease differentiation. Concurrently, CNN-based Vision Encoder extract discriminative hierarchical features, which are dy namically fused with textual representations via a multi-head attention mechanism, en suring adaptive cross-modal feature alignment. Unlike conventional fusion techniques, our approach learns complex inter-dependencies between textual cues and visual pat terns, enhancing classification accuracy and segmentation precision. Finally, we demon strate our proposed framework{u2019}seffectiveness byevaluating it on the Plant Disease Diag nosis Multimodal Dataset (PDDM) and achieving state-of-the-art (SOTA) segmentation and classification performance. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Plant pathology |
| General subdivision | Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Natural language processing (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Agriculture |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chutiporn Anutariya, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mongkol Ekpanyapong, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Cherdsak Kingkan, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | AIT Scholarship, |
| 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-25-05 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B23568">http://203.159.5.9/ait-thesis/detail.php?q=B23568</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b12476699 |
| b | mnarc |
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| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 260309 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 260218 |
| First date, FD (RLIN) | m |
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| -- | a |
| -- | 0 |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 67-Electronic Resource |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2026-02-18 |
| RECORD Id | RECORD # : i13573652 |
| LPATRON | LPATRON : 0 |
| LCHKIN | LCHKIN : - |
| RENEWALS | # RENEWALS : 0 |
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| -- | TOT CHKOUT : 0 |
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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 | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.DSAI-25-05 | 17/08/2026 | 1 | 17/08/2026 | 67-Electronic Resource |