Vqa and visual reasoning: An overview of recent datasets, methods and challenges
Artificial Intelligence (AI) and its applications have sparked extraordinary interest in recent
years. This achievement can be ascribed in part to advances in AI subfields including …
years. This achievement can be ascribed in part to advances in AI subfields including …
GraghVQA: Language-guided graph neural networks for graph-based visual question answering
Images are more than a collection of objects or attributes--they represent a web of
relationships among interconnected objects. Scene Graph has emerged as a new modality …
relationships among interconnected objects. Scene Graph has emerged as a new modality …
Enhancing e-commerce recommendation systems through approach of buyer's self-construal: necessity, theoretical ground, synthesis of a six-step model, and …
Y Feng - Frontiers in Artificial Intelligence, 2023 - frontiersin.org
The current recommendation system predominantly relies on evidential factors such as
behavioral outcomes and purchasing history. However, limited research has been …
behavioral outcomes and purchasing history. However, limited research has been …
Multi-step question-driven visual question answering for remote sensing
M Zhang, F Chen, B Li - IEEE Transactions on Geoscience and …, 2023 - ieeexplore.ieee.org
Visual question answering (VQA) aims to build an interactive system that infers the answer
according to the input image and text-based question. Recently, VQA for remote sensing has …
according to the input image and text-based question. Recently, VQA for remote sensing has …
SelfGraphVQA: a self-supervised graph neural network for scene-based question answering
BC de Oliveira Souza, M Aasan… - Proceedings of the …, 2023 - openaccess.thecvf.com
The intersection of vision and language is of major interest due to the increased focus on
seamless integration between recognition and reasoning. Scene graphs (SGs) have …
seamless integration between recognition and reasoning. Scene graphs (SGs) have …
Neuro-symbolic learning: Principles and applications in ophthalmology
Neural networks have been rapidly expanding in recent years, with novel strategies and
applications. However, challenges such as interpretability, explainability, robustness, safety …
applications. However, challenges such as interpretability, explainability, robustness, safety …
Medical visual question answering based on question-type reasoning and semantic space constraint
Medical visual question answering (Med-VQA) aims to accurately answer clinical questions
about medical images. Despite its enormous potential for application in the medical domain …
about medical images. Despite its enormous potential for application in the medical domain …
Herald: an annotation efficient method to detect user disengagement in social conversations
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging
conversation experience. User engagement is one of the most important metrics for …
conversation experience. User engagement is one of the most important metrics for …
SA-VQA: Structured alignment of visual and semantic representations for visual question answering
Visual Question Answering (VQA) attracts much attention from both industry and academia.
As a multi-modality task, it is challenging since it requires not only visual and textual …
As a multi-modality task, it is challenging since it requires not only visual and textual …
Research on visual question answering based on GAT relational reasoning
Y Miao, W Cheng, S He, H Jiang - Neural Processing Letters, 2022 - Springer
Due to the diversity of questions in VQA, it brings new challenges to the construction of VQA
model. Existing VQA models focus on constructing a new attention mechanism, which …
model. Existing VQA models focus on constructing a new attention mechanism, which …