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Found 8 papers, 1 papers with code
Implicit Sensing in Traffic Optimization: Advanced Deep Reinforcement Learning Techniques
The results unequivocally demonstrate that the DQN agent trained using the {\epsilon}-greedy policy significantly outperforms the one trained with the Boltzmann policy.
An Image Labeling Tool and Agricultural Dataset for Deep Learning
Images were annotated with segmentations for foreground leaf, fruit, and stem instances, and diseased leaf area.
Batch Normalization is a Cause of Adversarial Vulnerability
Batch normalization (batch norm) is often used in an attempt to stabilize and accelerate training in deep neural networks.
Predicting Adversarial Examples with High Confidence
It has been suggested that adversarial examples cause deep learning models to make incorrect predictions with high confidence.
Attacking Binarized Neural Networks
Neural networks with low-precision weights and activations offer compelling efficiency advantages over their full-precision equivalents.
The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment
An original dataset for semantic segmentation, Ciona17, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species in a marine environment.
An Integrated Simulator and Dataset that Combines Grasping and Vision for Deep Learning
Deep learning is an established framework for learning hierarchical data representations.
Modeling Grasp Motor Imagery through Deep Conditional Generative Models
Grasping is a complex process involving knowledge of the object, the surroundings, and of oneself.
