CNN deep learning-based image to vector depiction
In the computational science and engineering domains, the depiction of picture information
remains an intricate problem. Such a description needs an accurate recognition of various …
remains an intricate problem. Such a description needs an accurate recognition of various …
A survey of methods, datasets and evaluation metrics for visual question answering
Abstract Visual Question Answering (VQA) is a multi-disciplinary research problem that has
captured the attention of both computer vision as well as natural language processing …
captured the attention of both computer vision as well as natural language processing …
Surgical-vqa: Visual question answering in surgical scenes using transformer
Visual question answering (VQA) in surgery is largely unexplored. Expert surgeons are
scarce and are often overloaded with clinical and academic workloads. This overload often …
scarce and are often overloaded with clinical and academic workloads. This overload often …
Surgical-vqla: Transformer with gated vision-language embedding for visual question localized-answering in robotic surgery
Despite the availability of computer-aided simulators and recorded videos of surgical
procedures, junior residents still heavily rely on experts to answer their queries. However …
procedures, junior residents still heavily rely on experts to answer their queries. However …
See and learn more: Dense caption-aware representation for visual question answering
With the rapid development of deep learning models, great improvements have been
achieved in the Visual Question Answering (VQA) field. However, modern VQA models are …
achieved in the Visual Question Answering (VQA) field. However, modern VQA models are …
Can Textual Semantics Mitigate Sounding Object Segmentation Preference?
The Audio-Visual Segmentation (AVS) task aims to segment sounding objects in the visual
space using audio cues. However, in this work, it is recognized that previous AVS methods …
space using audio cues. However, in this work, it is recognized that previous AVS methods …
A study of convnext architectures for enhanced image captioning
This study explores the effectiveness of the ConvNeXt model, an advanced computer vision
architecture, in the task of image captioning. We integrated ConvNeXt with a Long Short …
architecture, in the task of image captioning. We integrated ConvNeXt with a Long Short …
Multilevel attention and relation network based image captioning model
H Sharma, S Srivastava - Multimedia Tools and Applications, 2023 - Springer
The aim of the image captioning task is to understand various semantic concepts such as
objects and their relationships in an image and combine them to generate a natural …
objects and their relationships in an image and combine them to generate a natural …
Improving visual question answering by combining scene-text information
The text present in natural scenes contains semantic information about its surrounding
environment. For example, the majority of questions asked by blind people related to images …
environment. For example, the majority of questions asked by blind people related to images …
Explainability in medical image captioning
R Beddiar, M Oussalah - Explainable Deep Learning AI, 2023 - Elsevier
Image captioning is the task of describing the content of the image using textual
representation. It has been used in many applications such as semantic tagging, image …
representation. It has been used in many applications such as semantic tagging, image …