Bias mitigation in image classification has been widely researched, and
...
The exploration of the latent space in StyleGANs and GAN inversion exemp...
Label-noise or curated unlabeled data is used to compensate for the
assu...
The exploration of the latent space in StyleGANs and GAN inversion exemp...
Lifelogging has gained more attention due to its wide applications, such...
Humans possess the capacity to reason about the future based on a sparse...
Story visualization advances the traditional text-to-image generation by...
Existing automatic story evaluation methods place a premium on story lex...
This paper explores the task of Temporal Video Grounding (TVG) where, gi...
There are several problems with the robustness of Convolutional Neural
N...
We introduce a challenging training scheme of conditional GANs, called
o...
Novel object captioning aims at describing objects absent from training ...
We push forward neural network compression research by exploiting a nove...
Generating texts in scientific papers requires not only capturing the co...
It is common practice for chemists to search chemical databases based on...
Story generation is a task that aims to automatically produce multiple
s...
Visual storytelling is a task of generating relevant and interesting sto...
Neural Module Network (NMN) is a machine learning model for solving the
...
Unsupervised learning can discover various unseen diseases, relying on
l...
Data augmentation policies drastically improve the performance of image
...
Model ensemble techniques often increase task performance in neural netw...
This work aims to identify/bridge the gap between Artificial Intelligenc...
Deep Neural Networks (DNNs) generalize well despite their massive size a...
Data augmentation methods are indispensable heuristics to boost the
perf...
Although neural machine translation models reached high translation qual...
Leveraging large-scale healthy datasets, unsupervised learning can disco...
Accurate computer-assisted diagnosis, relying on large-scale annotated
p...
Convolutional Neural Networks (CNNs) can achieve excellent computer-assi...
Prostate cancer is the most common malignant tumors in men but prostate
...
Prostate cancer is the most common cancer among US men. However, prostat...
Due to the lack of available annotated medical images, accurate
computer...
Accurate computer-assisted diagnosis using Convolutional Neural Networks...
Accurate computer-assisted diagnosis can alleviate the risk of overlooki...
The input method is an essential service on every mobile and desktop dev...
Object co-segmentation is the task of segmenting the same objects from
m...
Structural planning is important for producing long sentences, which is ...
Many studies have been undertaken by using machine learning techniques,
...
The success of deep learning in computer vision is mainly attributed to ...
Natural language processing (NLP) models often require a massive number ...
Neural machine translation models rely on the beam search algorithm for
...
For extended periods of time, sequence generation models rely on beam se...
Recently, the attention mechanism plays a key role to achieve high
perfo...
We propose an approach to build a neural machine translation system with...
Automatic image annotation has been an important research topic in
facil...