Search Results for author:
Found 11 papers, 2 papers with code
Quantitative knowledge retrieval from large language models
Large language models (LLMs) have been extensively studied for their abilities to generate convincing natural language sequences, however their utility for quantitative information retrieval is less well understood.
Confidence-Aware Learning Assistant
(2) With the help of 20 participants, we observed that correct answer rates of questions were increased by 14% and 17% by giving feedback about correct answers without confidence and incorrect answers with confidence, respectively.
Distortion-Adaptive Grape Bunch Counting for Omnidirectional Images
Because conventional object counting methods cannot handle the distortion of omnidirectional images, we propose to process them using stereographic projection, which enables conventional methods to obtain a good approximation of the density function.
Facial Landmark Detection for Manga Images
The topic of facial landmark detection has been widely covered for pictures of human faces, but it is still a challenge for drawings.
A survey of comics research in computer science
We propose in this paper to review the previous research about comics in computer science, to state what have been done and to give some insights about the main outlooks.
Multimedia
ShakeDrop Regularization for Deep Residual Learning
In this paper, to relieve the overfitting effect of ResNet and its improvements (i. e., Wide ResNet, PyramidNet, and ResNeXt), we propose a new regularization method called ShakeDrop regularization.
ShakeDrop regularization
This paper proposes a powerful regularization method named \textit{ShakeDrop regularization}.
Automatic Generation of Typographic Font from a Small Font Subset
The proposed method uses strokes from given samples for font generation.
Deep Pyramidal Residual Networks with Separated Stochastic Depth
On general object recognition, Deep Convolutional Neural Networks (DCNNs) achieve high accuracy.
A Generic Method for Automatic Ground Truth Generation of Camera-captured Documents
The method is generic, language independent and can be used for generation of labeled documents datasets (both scanned and cameracaptured) in any cursive and non-cursive language, e. g., English, Russian, Arabic, Urdu, etc.
Scalable Solution for Approximate Nearest Subspace Search
The existing methods for the problem are, however, useless in a large-scale problem with a large number of subspaces and high dimensionality of the feature space.
