My new journal paper “UNSUPERVISED ROTATION FACTORIZATION IN RESTRICTED BOLTZMANN MACHINES” is now available at HTTPS://IEEEXPLORE.IEEE.ORG/DOCUMENT/8870198. This paper shows a new method to learn rotation-invariant features on shallow neural network, without the necessity to use data augmentation. The paper shows mathematical and experimental proofs of its effectiveness.
Plant phenotyping is the identification of effects on plant structure and function (the phenotype) resulting from genotypic differences (i.e., differences in the genetic code) and the environmental conditions a plant has been exposed to. Knowledge Read more…
This workshop plans to showcase the challenges raised by working on computer vision for plant phenotyping and agriculture. Workshop goals include demonstrating the state-of-the-art, identifying key unsolved problems, and introducing computer scientists with an interest Read more…
Machine learning (ML) has been recognized as central to artificial intelligence (AI) for many decades. The question of how the things that have been learned in one context can be re-used and adapted in other Read more…