DELTA: Decoupling long-tailed online continual learning
A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of
models to rapidly learn new information in real-world scenarios where data follows long …
models to rapidly learn new information in real-world scenarios where data follows long …
Automatic recognition of food ingestion environment from the aim-2 wearable sensor
Detecting an ingestion environment is an important aspect of monitoring dietary intake. It
provides insightful information for dietary assessment. However it is a challenging problem …
provides insightful information for dietary assessment. However it is a challenging problem …
An improved encoder-decoder framework for food energy estimation
Dietary assessment is essential to maintaining a healthy lifestyle. Automatic image-based
dietary assessment is a growing field of research due to the increasing prevalence of image …
dietary assessment is a growing field of research due to the increasing prevalence of image …
Muti-stage hierarchical food classification
Food image classification serves as a fundamental and critical step in image-based dietary
assessment, facilitating nutrient intake analysis from captured food images. However …
assessment, facilitating nutrient intake analysis from captured food images. However …
Diffusion model with clustering-based conditioning for food image generation
Image-based dietary assessment serves as an efficient and accurate solution for recording
and analyzing nutrition intake using eating occasion images as input. Deep learning-based …
and analyzing nutrition intake using eating occasion images as input. Deep learning-based …
FMiFood: Multi-modal Contrastive Learning for Food Image Classification
Food image classification is the fundamental step in image-based dietary assessment,
which aims to estimate participants' nutrient intake from eating occasion images. A common …
which aims to estimate participants' nutrient intake from eating occasion images. A common …
Personalized food image classification: Benchmark datasets and new baseline
Food image classification is a fundamental step of image-based dietary assessment,
enabling automated nutrient analysis from food images. Many current methods employ deep …
enabling automated nutrient analysis from food images. Many current methods employ deep …
MFP3D: Monocular Food Portion Estimation Leveraging 3D Point Clouds
Food portion estimation is crucial for monitoring health and tracking dietary intake. Image-
based dietary assessment, which involves analyzing eating occasion images using …
based dietary assessment, which involves analyzing eating occasion images using …
SOOTYDEEPFIC: Food Item Classification Using Sooty Tern optimized Deep Learning Network.
Foods can be categorized based on their chemical composition, purpose, necessity,
concentration, and nutritional value. Protein, fat, and carbohydrates are all categorized as …
concentration, and nutritional value. Protein, fat, and carbohydrates are all categorized as …
Live Cell Imaging Analysis Using Machine Learning and Synthetic Food Image Generation
Y Han - 2024 - search.proquest.com
2.1 A phase contrast microscopy image of the cell sorting device or chip. The flow direction
is shown in red arrows. A stream of cells enters the chip from the bottom inlet, the …
is shown in red arrows. A stream of cells enters the chip from the bottom inlet, the …