Dat Tran
Head of AI
Axel Springer AI
location_on Germany
Member since 4 years
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Dat Tran
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Dat is the Head of AI at Axel Springer Ideas Engineering (https://axelspringerideas.de/), the innovation unit of Axel Springer SE which is the largest digital publishing house in Europe. He establishes and leads Axel Springer AI (https://ai.axelspringer.com/) where his goal is to make AI more accessible within Axel Springer and hence drive innovations within the group. His ultimate plan is to turn Axel Springer into an AI first company.
Dat's interests are diverse from traditional machine learning, deep learning, AI in general to computer vision. Previously, he co-headed the data team at idealo.de where he built up the machine learning team from scratch. His team mainly focused on computer vision problems from teaching a computer to understand aesthetics to upscaling low-resolution images. He is a regular speaker and has presented at several renowned conferences. He also blogs about his work on Medium. His background is in Operations Research and Econometrics. Dat received his MSc in Economics from Humboldt University of Berlin.
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imagededup - Finding duplicate images made easy!
Dat TranHead of AIAxel Springer AI
Tanuj JainSr. Machine Learning EngineerAxel Springer AIschedule 3 years ago
45 Mins
Talk
Beginner
The problem of finding duplicates in an image collection is widespread. Many online businesses rely on image galleries to deliver a good customer experience and consequently, generate more revenue. Hence, the image galleries need to be of the highest quality. Presence of duplicates in such galleries could potentially degrade the customer experience. Additionally, image-based machine learning models could generate misleading results due to the duplicates present in the training/evaluation/test sets.
Therefore, finding and removing duplicates is an important requirement across several use cases. In this talk, we want to present imagededup, a Python package we built to solve the problem of finding exact and near duplicates in an image collection. We will speak about the motivation behind building it, its functionality and also give a demo.
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Image ATM - Image Classification for Everyone
45 Mins
Talk
Intermediate
At idealo.de we store and display millions of images. Our gallery contains pictures of all sorts. You’ll find there vacuum cleaners, bike helmets as well as hotel rooms. Working with huge volume of images brings some challenges: How to organize the galleries? What exactly is in there? Do we actually need all of it?
To tackle these problems you first need to label all the pictures. In 2018 our Data Science team completed four projects in the area of image classification. In 2019 there were many more to come. Therefore, we decided to automate this process by creating a software we called Image ATM (Automated Tagging Machine). With the help of transfer learning, Image ATM enables the user to train a Deep Learning model without knowledge or experience in the area of Machine Learning. All you need is data and spare couple of minutes!
In this talk we will discuss the state-of-art technologies available for image classification and present Image ATM in the context of these technologies. We will then give a crash course of our product where we will guide you through different ways of using it - in shell, on Jupyter Notebook and on the Cloud. We will also talk about our roadmap for Image ATM.
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