A comprehensive survey on graph neural networks
Deep learning has revolutionized many machine learning tasks in recent years, ranging
from image classification and video processing to speech recognition and natural language …
from image classification and video processing to speech recognition and natural language …
[HTML][HTML] Graph neural networks: A review of methods and applications
Lots of learning tasks require dealing with graph data which contains rich relation
information among elements. Modeling physics systems, learning molecular fingerprints …
information among elements. Modeling physics systems, learning molecular fingerprints …
Visual semantic reasoning for image-text matching
Image-text matching has been a hot research topic bridging the vision and language areas.
It remains challenging because the current representation of image usually lacks global …
It remains challenging because the current representation of image usually lacks global …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Krisp: Integrating implicit and symbolic knowledge for open-domain knowledge-based vqa
One of the most challenging question types in VQA is when answering the question requires
outside knowledge not present in the image. In this work we study open-domain knowledge …
outside knowledge not present in the image. In this work we study open-domain knowledge …
Learning to compose dynamic tree structures for visual contexts
We propose to compose dynamic tree structures that place the objects in an image into a
visual context, helping visual reasoning tasks such as scene graph generation and visual …
visual context, helping visual reasoning tasks such as scene graph generation and visual …
A comprehensive survey of scene graphs: Generation and application
Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …
attributes, and relationships between objects in the scene. As computer vision technology …
Murel: Multimodal relational reasoning for visual question answering
R Cadene, H Ben-Younes, M Cord… - Proceedings of the …, 2019 - openaccess.thecvf.com
Multimodal attentional networks are currently state-of-the-art models for Visual Question
Answering (VQA) tasks involving real images. Although attention allows to focus on the …
Answering (VQA) tasks involving real images. Although attention allows to focus on the …
When radiology report generation meets knowledge graph
Automatic radiology report generation has been an attracting research problem towards
computer-aided diagnosis to alleviate the workload of doctors in recent years. Deep learning …
computer-aided diagnosis to alleviate the workload of doctors in recent years. Deep learning …
Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …
decision strategies. However, in many cases, it is desirable to learn directly from …