| Paper Title | DOI | Summary |
|---|---|---|
| Deep learning in food category recognition | 10.1016/j.inffus.2023.101859 | Focuses on deep learning for food category recognition. |
| DeepFood: Food Image Analysis and Dietary Assessment via Deep Model | 10.1109/ACCESS.2020.2973625 | Introduces DeepFood, a model for food image analysis and dietary assessment using deep learning. |
| A review on vision-based analysis for automatic dietary assessment | 10.1016/j.tifs.2022.02.017 | Offers a comprehensive review of vision-based analysis for automatic dietary assessment. |
| Analysis of Convolutional Neural Networks on Indian food detection and estimation of calories | 10.1016/j.matpr.2022.03.122 | Analyzes the use of CNNs for Indian food detection and calorie estimation. |
| Applying Image-Based Food-Recognition Systems on Dietary Assessment, A Systematic Review | 10.1093/advances/nmac078 | Systematic review of image-based food recognition systems for dietary assessment. |
| YOLO*C — Adding context improves YOLO performance | 10.1016/j.neucom.2023.126655 | How adding context enhances YOLO performance. |
| Small-object detection based on YOLOv5 in autonomous driving systems | 10.1016/j.patrec.2023.03.009 | Discusses small-object detection using YOLOv5 in autonomous driving systems. |
| Vision-based food nutrition estimation via RGB-D fusion network | 10.1016/j.foodchem.2023.136309 | Presents a method for food nutrition estimation using an RGB-D fusion network. |
| A Novel Ensemble Weight-Assisted Yolov5-Based Deep Learning Technique for the Localization and Detection of Malaria Parasites | 10.3390/electronics11233999 | Introduces a novel ensemble weight-assisted YOLOv5-based technique for detecting malaria parasites. |
| An Image Augmentation Method Based on Limited Samples for Object Tracking Based on Mobile Platform | 10.3390/s22051967 | Proposes an image augmentation method for object tracking on mobile platforms with limited samples. |
