marcel
Lausanne / Geneva, CH
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Challenges Entered
Completed
MineRL Labs - Carnegie Mellon University
Sample-efficient reinforcement learning in Minecraft
Latest submissions
Institute of Global Health
LifeCLEF
Classify images of snake species from around the world
Latest submissions
SBB
Multi Agent Reinforcement Learning on Trains.
Latest submissions
Seerave Foundation
A benchmark for image-based food recognition
Latest submissions
Stanford Neuromuscular Biomechanics Laboratory
Reinforcement Learning on Musculoskeletal Models
Latest submissions
Unity Technologies
A new benchmark for Artificial Intelligence (AI) research in Reinforcement Learning
Latest submissions
- May 16, 2020
- May 16, 2020
- May 16, 2020
- May 16, 2020
- May 16, 2020
About the Food Recognition Challenge
7 months agoHi @gloria_macia_munoz - some of the segmentations, as the one you identified, have been done by humans under time constraints. Those can certainly be improved. As we get better and better algorithms, more and more high quality data will become available for this challenge, in future rounds. It’s very important to note that this will be a long-term challenge / benchmark. This is just the first round, with the data that was provided. Over time, both the quantity and the quality will increase.