Project

5th International workshop on "Data Engineering meets Intelligent Food and COoking Recipe" (DECOR)

Goal: The past decade has seen an enormous growth in the research related to the digital food and cooking recipes underpinnings of data engineering, as food is essential for human life and related health. The ability to collect, store, process, and evaluate cooking recipes has advanced immeasurably, and data science-driven methods have had unprecedented impact on food experience sharing and recommendations at large, mainly because of their success in analys-ing and predicting human cooking expectation, flavour, and taste preferences. Data Engineering stands to benefit from the food computing and recipe cooking revolution in similar ways, but realizing this vision requires thoughtful and concerted effort. The 5th International Workshop on Data Engineering meets Intelligent Food and COoking Recipes (DECOR@ICDE2022) aims to accelerate research in data science by providing a forum for the latest innovations in the intersection of Data Engineering and Intelligent Food and Cooking Recipes. The workshop is specifically focusing on data science innovations that accelerate the organization, integra-tion, access, and sharing of digital objects in support of the Intelligent Food and Cooking Reci-pes domain. This domain comprises not only the process of cooking, but also includes intelli-gent methods for enhancing human-food interactions, ranging from devising technology, playful interactions, multisensory experience design, understanding cross-cultural food eating habits and perception, as well as food choices and their health connections. Consequently, increas-ing the ability of influencing food eating habits and choices that promote, simultaneously, healthful eating-decisions and creative new human-food interaction experiences.

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Frederic Andres
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Deepanshu Pandey, Purva Parmar, Gauri Toshniwal, Mansi Goel, Vishesh Agrawal, Shivangi Dhiman, Lavanya Gupta and Ganesh Bagler, IIIT-Delhi, India. “Object Detection in Indian Food Platters using Transfer Learning with YOLOv4”
 
Frederic Andres
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Hiroshi Uehara (Rissho University) and Daichi Mochihashi (The Institute of Statistical Mathematics), Japan. “Detecting Sensory Textures with Rheological Characteristics from Recipe Sharing Sites”
 
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Keynote I: "Addressing the food image challenge as a fine-grained recognition problem" by Professor Dr. Petia RADEVA (Consolidated Research Group “Computer Vision and Machine Learning” at the University of Barcelona (CVMLUB))
Abstract: Food is an integral part of a healthy lifestyle. Recent advancements in Computer Vision and Deep Learning algorithms have given rise to several food analysis applications aimed at developing better nutritional habits. Food images have high degree of ambiguity and inter-class similarity, being really difficult to distinguish the food categories even for humans. We address the problem of food recognition as a fine-grained recognition problem where the main goal is to focus on subtle discriminative details to distinguish similar classes. Multiple specialized transformer blocks focus on specific subsets of food categories that are specially difficult to distinguish. We apply our method on three public datasets, namely: Food1K with 1000 classes, FoodX-251 with 251 classes and Food101 with 101 classes. Our validation shows that our method outperforms the state-of-the-art on the three public food recognition datasets containing fine-grained data.
Bio: Prof. Petia Radeva is a Full professor at the Universitat de Barcelona (UB), Head of the Consolidated Research Group “Computer Vision and Machine Learning” at the University of Barcelona (CVMLUB) at UB (www.ub.edu/cvmlub) and Senior researcher in Computer Vision Center (www.cvc.uab.es). She was PI of UB in 7 European, 3 international and more than 25 national projects devoted to applying Computer Vision and Machine learning for real problems like food intake monitoring (e.g. for patients with kidney transplants and for older people). Petia Radeva is a REA-FET-OPEN vice-chair since 2015 on, and international mentor in the Wild Cards EIT program since 2017. She is an Associate editor of Pattern Recognition journal (Q1, IP=7.196) and International Journal of Visual Communication and Image Representation (Q2, IP=3.13). She is a Research Manager of the State Agency of Research (Agencia Estatal de Investigación, AEI) of the Ministry of Science and Innovation of Spain. Petia Radeva belongs to the top 2% of the World ranking of scientists with the major impact in the field of TIC according to the citations indicators of the popular ranking of Stanford. Moreover, she was awarded IAPR Fellow since 2015, ICREA Academia assigned to the 30 best scientists in Catalonia for her scientific merits since 2014, received several international awards (“Aurora Pons Porrata” of CIARP, Prize “Antonio Caparrós” for the best technology transfer of UB, etc). She supervised 22 PhD students and published more than 100 SCI journal publications and 250 international chapters and proceedings, her Google scholar h-index is 50 with more than 9000 cites.
 
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Keynote II: "Pervasive dietary monitoring with wearable cameras and AI” by Dr. Benny LO (Hamlyn Centre/Dept of Surgery and Cancer, Imperial College, UK)
Abstract: Most of the current dietary assessment methods rely on the individual’s own record, such as 24 hrs recall, and which often led to subjective and inaccurate measurements. Although there are some objective and accurate measurement methods, such as the use of doubly labelled water, weighted food record etc., these are either very expensive or can only be conducted in a highly controlled environment. These methods often fail to reveal the actual nutrient intake in the population. Given the advances in smartphone technologies, new software tools and mobile applications have been introduced for users to log and record their food intakes. Although these tools ease the recording of information, such active approach relies mainly on the users’ input which could be subjective and may miss some crucial information for dietary assessments. To address the need for accurate objective dietary assessment, we have introduced the passive approach in dietary monitoring with low-cost wearable cameras. The wearable cameras are designed to be worn on the glasses or pinned on the chest, and they can continuously capture snapshots throughout the day. Hence, the cameras will be able to capture all the eating activities of the users and other daily activities. In addition, to quantify the dietary intake from the images captured, novel AI methods have been developed to recognise the food items, estimate portion sizes, and deduce the nutrient intakes of the participants. With the support from the Bill and Melinda Gates Foundation, large scale studies are being carried out to assess the feasibility and effectiveness of such passive dietary monitoring approach in both rural and urban areas in two African countries, namely Uganda and Ghana. In this talk, I will briefly introduce the concept of passive dietary monitoring approach, present some of our recent work developed, and discuss the challenges faced in collecting/analysing data for estimating the individual dietary intake in our field studies.
Bio: Dr Benny Lo, PhD is a Senior Lecturer of the Hamlyn Centre/Dept of Surgery and Cancer, Imperial College. His research mainly focuses on Body Sensor Networks, Pervasive Sensing, Biomedical Engineering, Micro-Electronics, Surgical Vision, and Machine Learning for healthcare, well-being and sports applications. He is one of the pioneers in pervasive sensing research and led a number of the translational projects on applying sensing technologies in clinical applications. His research work has been highly recognised by academic and industrial and led to numerous awards, such as the Best Paper award at BSN2021, the FAU’s Open Challenge, etc. He is an Associate Editor of the IEEE Journal of Biomedical and Health Informatics (J-BHI) and the Topics Editor of the International Journal of Distributed Sensor Networks (IJDSN). He was the Past Chair of the IEEE EMBS Wearable Biomedical Sensors and Systems (WBSS) Technical Committee 2018-19 and a Steering Committee member of the IEEE EMBS Standards Technical Committee.
 
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When: May 9, 2022 MYT  From 8:00 am MYT (8 pm EST on May 8th; 2 am CEST) to 6:00 pm MYT (6 am EST; noon CEST) Delivery mode / Platform: Fully virtual/Zoom (Kuala Lumpur, Malaysia) The safety and well-being of all conference participants are a priority, and the decision has been made to hold DECOR2022@ICDE as an online event.
The full program can be seen @Workshop webpage @ http://research.nii.ac.jp/decor/DECOR2022program.html
Workshop registration is required. Register Today@ https://web.cvent.com/event/7612d523-dbf6-422e-8e85-99cecc686f19/summary
Join and enjoy DECOR2022, a premier international workshop features world-class keynotes and several papers authored by leading experts from different continents. Keynote Speakers: ★  First keynote talk         “Addressing the food image challenge as a fine-grained recognition problem,”         Prof. P. Radeva, Universitat de Barcelona (UB) & Computer Vision Center (UAB), Spain. ★  Second keynote talk: “Pervasive dietary monitoring with wearable cameras and AI,”  Dr. Benny Lo, Faculty of Medicine, Department of Surgery & Cancer, Imperial college, UK. Special Events: ★    Special Social Session. “Food Expectation: Truly Malaysia Cuisine Experience,”             Professor M. S. Karim, Universiti Putra Malaysia, Malaysia. ★    Panel Discussion Session on Intelligent Food and Data Engineering.
 
Frederic Andres
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Call for paper: The 5th International Workshop on Data Engineering meets Intelligent Food and COoking Recipes (DECOR@ICDE2022)
First round
January 14, 2022: Full Paper, demo, short paper First round Submissions due
February 5, 2022: First Round Acceptance Notification
February 18, 2022: First Round Revision Submission due
March 4, 2022: First Round Final Notification
Second round
February 15 2022: Full Paper, demo, short paper Second round Submissions due
February 29, 2022: Second Round Acceptance Notification
March 12, 2022: Second Round Revision Submission due
March 16, 2022: Second Round Final Notification
for all DECOR 2022 Accepted papers, demo or short papers March 30, 2022 DECOR Camera-ready papers due May 9, 2022 Workshop 100% online organisation
 
Frederic Andres
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First round
January 14, 2022: Full Paper, demo, short paper First round Submissions due
February 5, 2022: First Round Acceptance Notification
February 18, 2022: First Round Revision Submission due
March 4, 2022: First Round Final Notification
Second round
February 15 2022: Full Paper, demo, short paper Second round Submissions due
February 29, 2022: Second Round Acceptance Notification
March 12, 2022: Second Round Revision Submission due
March 16, 2022: Second Round Final Notification
for all DECOR 2022 Accepted papers, demo or short papers
March 30, 2022 DECOR Camera-ready papers due
May 9, 2022 Workshop 100% online organisation
 
Frederic Andres
added an update
The 5th International Workshop on Data Engineering meets Intelligent Food and COoking Recipes (DECOR@ICDE2022) aims to accelerate research in data science by providing a forum for the latest innovations in the intersection of Data Engineering and Intelligent Food and Cooking Recipes.
 
Frederic Andres
added a project goal
The past decade has seen an enormous growth in the research related to the digital food and cooking recipes underpinnings of data engineering, as food is essential for human life and related health. The ability to collect, store, process, and evaluate cooking recipes has advanced immeasurably, and data science-driven methods have had unprecedented impact on food experience sharing and recommendations at large, mainly because of their success in analys-ing and predicting human cooking expectation, flavour, and taste preferences. Data Engineering stands to benefit from the food computing and recipe cooking revolution in similar ways, but realizing this vision requires thoughtful and concerted effort. The 5th International Workshop on Data Engineering meets Intelligent Food and COoking Recipes (DECOR@ICDE2022) aims to accelerate research in data science by providing a forum for the latest innovations in the intersection of Data Engineering and Intelligent Food and Cooking Recipes. The workshop is specifically focusing on data science innovations that accelerate the organization, integra-tion, access, and sharing of digital objects in support of the Intelligent Food and Cooking Reci-pes domain. This domain comprises not only the process of cooking, but also includes intelli-gent methods for enhancing human-food interactions, ranging from devising technology, playful interactions, multisensory experience design, understanding cross-cultural food eating habits and perception, as well as food choices and their health connections. Consequently, increas-ing the ability of influencing food eating habits and choices that promote, simultaneously, healthful eating-decisions and creative new human-food interaction experiences.