1.

Record Nr.

UNINA9910132599903321

Autore

Labrecque Marie-France

Titolo

Yucatán 1973-1974 : le terrain en milieu rural et prolétaire / / Marie-France Labrecque

Pubbl/distr/stampa

Chicoutimi : , : J.-M. Tremblay, , 2008

ISBN

1-4123-6296-2

Descrizione fisica

1 online resource

Collana

Classiques des sciences sociales ; ; 3219

Disciplina

306.3

Soggetti

Economic anthropology - Mexico

Lingua di pubblicazione

Francese

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910683343703321

Titolo

Image Based Computing for Food and Health Analytics: Requirements, Challenges, Solutions and Practices : IBCFHA / / edited by Rajeev Tiwari, Deepika Koundal, Shuchi Upadhyay

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

9783031229596

9783031229589

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (247 pages)

Disciplina

394.12

610.285

Soggetti

Food science

Biomedical engineering

Medical informatics

Artificial intelligence

Application software

Food Science

Food Engineering

Medical and Health Technologies

Health Informatics



Artificial Intelligence

Computer and Information Systems Applications

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

1. Food Computing Research opportunities using AI and M -- Estimating the Risk of Diabetes Using Association Rule Mining Based on Clustering -- Digital Twins for Food Nutrition and Health Based on Cloud Communication -- Smart Healthcare Systems: An IoT with Fog Computing based Solution for Healthcare,- An Intelligent and Secure Real-time Environment Monitoring System for healthcare using IoT and Cloud Computing with the Mobile Application Support -- Efficient BREV Ensemble Framework: A Case Study of Breast Cancer Prediction,- Current and Future Trends of Cloud-based solutions for Healthcare,- Secure Authentication in IoT based healthcare management environment using integrated Fog computing enabled blockchain system -- SENTIMENT ANALYSIS OF COVID-19 TWEETS USING VOTING ENSEMBLE-BASED MODEL -- Cloud and machine learning based solutions for healthcare and preventio -- Interoperable Cloud-Fog architecture in IoT-enabled Health Sector -- COVID-19 Wireless Self-Assessment Software for Rural Areas in Nigeria -- Efficient Fog-to-Cloud Internet-of-Medical-Things System.

Sommario/riassunto

Image Based Computing for Food and Health Analytics covers the current status of food image analysis and presents computer vision and image processing based solutions to enhance and improve the accuracy of current measurements of dietary intake. Many solutions are presented to improve the accuracy of assessment by analyzing health images, data and food industry based images captured by mobile devices. Key technique innovations based on Artificial Intelligence and deep learning-based food image recognition algorithms are also discussed.