[HTML][HTML] Vision-based methods for food and fluid intake monitoring: a literature review

X Chen, EN Kamavuako - Sensors, 2023 - mdpi.com
Food and fluid intake monitoring are essential for reducing the risk of dehydration,
malnutrition, and obesity. The existing research has been preponderantly focused on dietary …

[HTML][HTML] Thought on food: A systematic review of current approaches and challenges for food intake detection

PA Neves, J Simões, R Costa, L Pimenta… - Sensors, 2022 - mdpi.com
Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the
early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise …

[HTML][HTML] Fight fire with fire: Detecting forest fires with embedded machine learning models dealing with audio and images on low power IoT devices

G Peruzzi, A Pozzebon, M Van Der Meer - Sensors, 2023 - mdpi.com
Forest fires are the main cause of desertification, and they have a disastrous impact on
agricultural and forest ecosystems. Modern fire detection and warning systems rely on …

[HTML][HTML] Optimized deep learning algorithms for tomato leaf disease detection with hardware deployment

H Tarek, H Aly, S Eisa, M Abul-Soud - Electronics, 2022 - mdpi.com
Smart agriculture has taken more attention during the last decade due to the bio-hazards of
climate change impacts, extreme weather events, population explosion, food security …

[HTML][HTML] Machine learning modeling practices to support the principles of AI and ethics in nutrition research

DM Thomas, S Kleinberg, AW Brown, M Crow… - Nutrition & …, 2022 - nature.com
Background Nutrition research is relying more on artificial intelligence and machine learning
models to understand, diagnose, predict, and explain data. While artificial intelligence and …

Egocentric Human Activities Recognition with Multi-modal Interaction Sensing

Y Hao, A Kanezaki, I Sato, R Kawakami… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Egocentric human activity recognition (ego-HAR) has received attention in fields where
human intentions in a video must be estimated. However, the performance of existing …

[HTML][HTML] Food/non-Food classification of real-life egocentric images in low-and middle-income countries based on image tagging features

G Chen, W Jia, Y Zhao, ZH Mao, B Lo… - Frontiers in Artificial …, 2021 - frontiersin.org
Malnutrition, including both undernutrition and obesity, is a significant problem in low-and
middle-income countries (LMICs). In order to study malnutrition and develop effective …

Reduction of feature extraction for COVID-19 CXR using depthwise separable convolution network

Z Iklima, TM Kadarina, R Priambodo - Journal of Electronics …, 2022 - jeeemi.org
Abstract A Convolutional Neural Network (CNN) classifier is generally utilized to classify an
image tensor according to the mapped labels. The simplification of the classifier causes …

Social Environmental Predictors of Lapse in Dietary Behavior: An Ecological Momentary Assessment Study Amongst Dutch Adults Trying to Lose Weight

EM Roordink, IHM Steenhuis, W Kroeze… - Annals of Behavioral …, 2023 - academic.oup.com
Background When losing weight, most individuals find it difficult to maintain a healthy diet.
Social environmental conditions are of pivotal importance in determining dietary behavior …

[HTML][HTML] Capturing children food exposure using wearable cameras and deep learning

S Elbassuoni, H Ghattas, J El Ati, Y Zoughby… - PLOS Digital …, 2023 - journals.plos.org
Children's dietary habits are influenced by complex factors within their home, school and
neighborhood environments. Identifying such influencers and assessing their effects is …