相关论文: IMVB7t: A Multi-Modal Model for Food Preferences b…

Diet management is key to managing chronic diseases such as diabetes. Automated food recommender systems may be able to assist by providing meal recommendations that conform to a user's nutrition goals and food preferences. Current…

Humans routinely infer taste, smell, texture, and even sound from food images a phenomenon well studied in cognitive science. However, prior vision language research on food has focused primarily on recognition tasks such as meal…

Food is central to life. Food provides us with energy and foundational building blocks for our body and is also a major source of joy and new experiences. A significant part of the overall economy is related to food. Food science,…

A key challenge in robotic food manipulation is modeling the material properties of diverse and deformable food items. We propose using a multimodal sensory approach to interact and play with food that facilitates the ability to distinguish…

With the exponential growth in the usage of social media to share live updates about life, taking pictures has become an unavoidable phenomenon. Individuals unknowingly create a unique knowledge base with these images. The food images, in…

Understanding the pathways through which diet affects human metabolism is a central task in nutritional epidemiology. This article proposes novel methodology to identify food items associated with blood metabolites in two cohorts of…

Food recommender systems play an important role in assisting users to identify the desired food to eat. Deciding what food to eat is a complex and multi-faceted process, which is influenced by many factors such as the ingredients,…

Background: People's health depends on the use of proper diet as an important factor. Today, with the increasing mechanization of people's lives, proper eating habits and behaviors are neglected. On the other hand, food recommendations in…

Recent advances in artificial intelligence promote a wide range of computer vision applications in many different domains. Digital cameras, acting as human eyes, can perceive fundamental object properties, such as shapes and colors, and can…

Food authenticity studies are concerned with determining if food samples have been correctly labeled or not. Discriminant analysis methods are an integral part of the methodology for food authentication. Motivated by food authenticity…

This paper utilizes a machine learning model to estimate the consumer's behavior for food products with innovative transportation certificates in the U.S. Building on previous research that examined demand for food products with supply…

Experiencing food craving is nearly ubiquitous and has several negative pathological impacts, but effective intervention strategies to control or reverse craving remain limited. Food cue-reactivity tasks are often used to study food craving…

Diversity of food and its attributes represents the culinary habits of peoples from different countries. Thus, this paper addresses the problem of identifying food culture of people around the world and its flavor by classifying two main…

Experiments involving sensory analysis of foods and beverages are beneficial for selecting healthy products and assessing the preferences of potential consumers. They are generally planned in incomplete blocks, and their attributes, such as…

Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them. In the domain of clothing recommendation, incorporating items' visual…

It is well known that dietary habits have a significant influence on health. While many studies have been conducted to understand this relationship, little is known about the relationship between eating environments and health. Yet…

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 where human-based reviewing can be tedious, and…

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. A…

In visual decision making, high-level features, such as object categories, have a strong influence on choice. However, the impact of low-level features on behavior is less understood partly due to the high correlation between high- and…

Personality computing and affective computing, where the recognition of personality traits is essential, have gained increasing interest and attention in many research areas recently. We propose a novel approach to recognize the Big Five…