Zobrazeno 1 - 10
of 286
pro vyhledávání: '"Jürgen Schmidhuber"'
Autor:
Lukas Tuggener, Raphael Emberger, Adhiraj Ghosh, Pascal Sager, Yvan Putra Satyawan, Javier Montoya, Simon Goldschagg, Florian Seibold, Urs Gut, Philipp Ackermann, Jürgen Schmidhuber, Thilo Stadelmann
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 7, Iss 1, Pp 1–14-1–14 (2024)
We present solutions to two of the most pressing issues in contemporary optical music recognition (OMR). We improve recognition accuracy on low-quality, real-world (i.e. containing ageing, lighting, or dirt artefacts among others) input data and prov
Externí odkaz:
https://doaj.org/article/d568dd7db8a44636850f06f5348683ac
Publikováno v:
Frontiers in Computer Science, Vol 4 (2022)
Classification performance based on ImageNet is the de-facto standard metric for CNN development. In this work we challenge the notion that CNN architecture design solely based on ImageNet leads to generally effective convolutional neural network (CN
Externí odkaz:
https://doaj.org/article/83fe425baa3a4b4f8d78ca4670410700
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 9 (2012)
We present a combined machine learning and computer vision approach for robots to localize objects. It allows our iCub humanoid to quickly learn to provide accurate 3D position estimates (in the centimetre range) of objects seen. Biologically inspire
Externí odkaz:
https://doaj.org/article/20ac8f484c8c40b99be323f163729e80
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
We study unsupervised and supervised recognition of human actions in video sequences. The videos are represented by probability distributions and then meaningfully compared in a probabilistic framework. We introduce two novel approaches outperforming
Externí odkaz:
https://doaj.org/article/bf99207b6f7643d9b60846891fe3f47f
Publikováno v:
Neural Computation. 34:2232-2272
An agent in a nonstationary contextual bandit problem should balance between exploration and the exploitation of (periodic or structured) patterns present in its previous experiences. Handcrafting an appropriate historical context is an attractive al
Publikováno v:
Neural Computation. 33:1498-1553
A reinforcement learning agent that needs to pursue different goals across episodes requires a goal-conditional policy. In addition to their potential to generalize desirable behavior to unseen goals, such policies may also enable higher-level planni
Publikováno v:
Neural Networks. 130:309-325
Deep generative models seek to recover the process with which the observed data was generated. They may be used to synthesize new samples or to subsequently extract representations. Successful approaches in the domain of images are driven by several
Autor:
Jürgen Schmidhuber
Publikováno v:
Neural Networks. 127:58-66
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One network learns to generate a probability distribution over outputs, the
Reinforcement learning agents must generalize beyond their training experience. Prior work has focused mostly on identical training and evaluation environments. Starting from the recently introduced Crafter benchmark, a 2D open world survival game, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d88f01203f7e376c3783b3537b83c4d1
Autor:
Noor Sajid, Francesco Faccio, Lancelot Da Costa, Thomas Parr, Jürgen Schmidhuber, Karl Friston
Under the Bayesian brain hypothesis, behavioral variations can be attributed to different priors over generative model parameters. This provides a formal explanation for why individuals exhibit inconsistent behavioral preferences when confronted with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d05f7914178b7ddf0fdedc431e363327