We introduce Net2Brain, a graphical and command-line user interface tool...
Assessing the trustworthiness of artificial intelligence systems require...
Today's state of the art visual navigation agents typically consist of l...
We tackle the novel problem of incremental unsupervised domain adaptatio...
In this work, we propose different variants of the self-attention based
...
In this paper, we tackle an open research question in transfer learning,...
Scene text recognition models have advanced greatly in recent years. Ins...
In this paper, we adapt triplet neural networks (TNNs) to a regression t...
Action recognition is a key problem in computer vision that labels video...
We present an approach to tackle the speaker recognition problem using
T...
The goal of this study is to develop and analyze multimodal models for
p...
In the last decade, artificial intelligence (AI) models inspired by the ...
Transfer learning is widely used in deep neural network models when ther...
Convolutional Neural Networks (CNNs) have been proven to be extremely
su...
Deep learning techniques have become the to-go models for most vision-re...
Recently, the introduction of the generative adversarial network (GAN) a...
Crowding is a visual effect suffered by humans, in which an object that ...
We show that the algorithm to extract diverse M -solutions from a Condit...
In a series of papers by Dai and colleagues [1,2], a feature map (or ker...
Superpixel algorithms aim to over-segment the image by grouping pixels t...
Support Vector Machines (SVMs) are powerful learners that have led to
st...