IMVB7t: A Multi-Modal Model for Food Preferences based on Artificially Produced Traits
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866929748275363840 |
|---|---|
| author | Abir, Mushfiqur Rahman Hosain, Md. Tanzib Abdullah-Al-Jubair, Md. Mridha, M. F. |
| author_facet | Abir, Mushfiqur Rahman Hosain, Md. Tanzib Abdullah-Al-Jubair, Md. Mridha, M. F. |
| contents | Human behavior and interactions are profoundly influenced by visual stimuli present in their surroundings. This influence extends to various aspects of life, notably food consumption and selection. In our study, we employed various models to extract different attributes from the environmental images. Specifically, we identify five key attributes and employ an ensemble model IMVB7 based on five distinct models for some of their detection resulted 0.85 mark. In addition, we conducted surveys to discern patterns in food preferences in response to visual stimuli. Leveraging the insights gleaned from these surveys, we formulate recommendations using decision tree for dishes based on the amalgamation of identified attributes resulted IMVB7t 0.96 mark. This study serves as a foundational step, paving the way for further exploration of this interdisciplinary domain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16807 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | IMVB7t: A Multi-Modal Model for Food Preferences based on Artificially Produced Traits Abir, Mushfiqur Rahman Hosain, Md. Tanzib Abdullah-Al-Jubair, Md. Mridha, M. F. Computer Vision and Pattern Recognition Human behavior and interactions are profoundly influenced by visual stimuli present in their surroundings. This influence extends to various aspects of life, notably food consumption and selection. In our study, we employed various models to extract different attributes from the environmental images. Specifically, we identify five key attributes and employ an ensemble model IMVB7 based on five distinct models for some of their detection resulted 0.85 mark. In addition, we conducted surveys to discern patterns in food preferences in response to visual stimuli. Leveraging the insights gleaned from these surveys, we formulate recommendations using decision tree for dishes based on the amalgamation of identified attributes resulted IMVB7t 0.96 mark. This study serves as a foundational step, paving the way for further exploration of this interdisciplinary domain. |
| title | IMVB7t: A Multi-Modal Model for Food Preferences based on Artificially Produced Traits |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2412.16807 |