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Found 7 papers, 0 papers with code
On Randomized Classification Layers and Their Implications in Natural Language Generation
In natural language generation tasks, a neural language model is used for generating a sequence of words forming a sentence.
A Baseline for Detecting Out-of-Distribution Examples in Image Captioning
Image captioning research achieved breakthroughs in recent years by developing neural models that can generate diverse and high-quality descriptions for images drawn from the same distribution as training images.
Redesigning the classification layer by randomizing the class representation vectors
We propose to draw the class vectors randomly and set them as fixed during training, thus invalidating the visual similarities encoded in these vectors.
Joint Visual-Textual Embedding for Multimodal Style Search
We propose a method to retrieve similar items, based on a query item image and textual refinement properties.
Generating Diverse and Informative Natural Language Fashion Feedback
In this paper, we consider the task of generating natural language fashion feedback on outfit images.
Out-of-Distribution Detection using Multiple Semantic Label Representations
Deep Neural Networks are powerful models that attained remarkable results on a variety of tasks.
Actigraphy-based Sleep/Wake Pattern Detection using Convolutional Neural Networks
In order to study the connection between sleep/wake patterns and a cluster headache disorder, activity data was collected using a wearable device in the course of a clinical trial.
