Search Results for author:
Found 5 papers, 3 papers with code
Pay attention to the activations: a modular attention mechanism for fine-grained image recognition
Attention has been typically implemented in neural networks by selecting the most informative regions of the image that improve classification.
Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery
We propose a novel attention mechanism to enhance Convolutional Neural Networks for fine-grained recognition.
Ranked #106 on
Image Classification
on CIFAR-100
(using extra training data)
Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Following this trend on visual-based social analysis, we present a novel methodology based on Deep Learning to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits.
A Painless Attention Mechanism for Convolutional Neural Networks
We propose a novel attention mechanism to enhance Convolutional Neural Networks for fine-grained recognition.
Regularizing CNNs with Locally Constrained Decorrelations
In this paper, we show that regularizing negatively correlated features is an obstacle for effective decorrelation and present OrthoReg, a novel regularization technique that locally enforces feature orthogonality.
