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Full-Text Articles in Engineering
Figure-Ground Organization Using 3d Symmetry, Aaron Michaux, Vijai Jayadevan, Edward Delp, Zygmunt Pizlo
Figure-Ground Organization Using 3d Symmetry, Aaron Michaux, Vijai Jayadevan, Edward Delp, Zygmunt Pizlo
MODVIS Workshop
We present a novel approach to object localization using mirror symmetry as a general purpose and biologically motivated prior. 3D symmetry leads to good segmentation because (i) almost all objects exhibit symmetry, and (ii) configurations of objects are not likely to be symmetric unless they share some additional relationship. Furthermore, psychophysical evidence suggests that the human vision system makes use symmetry in constructing 3D percepts, indicating that symmetry may be important in object localization. No general purpose approach is known for solving 3D symmetry correspondence in 2D camera images, because few invariants exist. Therefore, to test symmetry as a clustering …
Model-Free Method Of Reinforcement Learning For Visual Tasks, Jeff S. Soldate, Jonghoon Jin, Eugenio Culurciello
Model-Free Method Of Reinforcement Learning For Visual Tasks, Jeff S. Soldate, Jonghoon Jin, Eugenio Culurciello
The Summer Undergraduate Research Fellowship (SURF) Symposium
There has been success in recent years for neural networks in applications requiring high level intelligence such as categorization and assessment. In this work, we present a neural network model to learn control policies using reinforcement learning. It takes a raw pixel representation of the current state and outputs an approximation of a Q value function made with a neural network that represents the expected reward for each possible state-action pair. The action is chosen an \epsilon-greedy policy, choosing the highest expected reward with a small chance of random action. We used gradient descent to update the weights and biases …