The multi-modal fusion in visual question answering: a review of attention mechanisms
Abstract Visual Question Answering (VQA) is a significant cross-disciplinary issue in the
fields of computer vision and natural language processing that requires a computer to output …
fields of computer vision and natural language processing that requires a computer to output …
Explaining explanations: An overview of interpretability of machine learning
There has recently been a surge of work in explanatory artificial intelligence (XAI). This
research area tackles the important problem that complex machines and algorithms often …
research area tackles the important problem that complex machines and algorithms often …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
A general survey on attention mechanisms in deep learning
G Brauwers, F Frasincar - IEEE Transactions on Knowledge …, 2021 - ieeexplore.ieee.org
Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …
models across many different domains and tasks. This survey provides an overview of the …
Gqa: A new dataset for real-world visual reasoning and compositional question answering
DA Hudson, CD Manning - … of the IEEE/CVF conference on …, 2019 - openaccess.thecvf.com
We introduce GQA, a new dataset for real-world visual reasoning and compositional
question answering, seeking to address key shortcomings of previous VQA datasets. We …
question answering, seeking to address key shortcomings of previous VQA datasets. We …
Unmasking Clever Hans predictors and assessing what machines really learn
Current learning machines have successfully solved hard application problems, reaching
high accuracy and displaying seemingly intelligent behavior. Here we apply recent …
high accuracy and displaying seemingly intelligent behavior. Here we apply recent …
Counterfactual vqa: A cause-effect look at language bias
Recent VQA models may tend to rely on language bias as a shortcut and thus fail to
sufficiently learn the multi-modal knowledge from both vision and language. In this paper …
sufficiently learn the multi-modal knowledge from both vision and language. In this paper …
Salient object detection in the deep learning era: An in-depth survey
As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …
increasing amount of research attention over the years. Recent advances in SOD are …
A multidisciplinary survey and framework for design and evaluation of explainable AI systems
The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …
Cascade r-cnn: Delving into high quality object detection
Z Cai, N Vasconcelos - … of the IEEE conference on computer …, 2018 - openaccess.thecvf.com
In object detection, an intersection over union (IoU) threshold is required to define positives
and negatives. An object detector, trained with low IoU threshold, eg 0.5, usually produces …
and negatives. An object detector, trained with low IoU threshold, eg 0.5, usually produces …