Integrating deep learning for visual question answering in ...

[PDF] Deep Learning Approaches for Improving Question Answering ...

Deep Learning Approaches for Improving Question Answering Systems in Hepatocellular Carcinoma Research · Shuning Huo, Yafei Xiang, +2 authors. Yulu Gong ...

Deep learning-based bridge damage cause estimation from multiple ...

In addition, datasets for VQA generally have multiple questions for a single image; Visual Question Answering (VQA) (Antol et al., Citation2015) is a widely ...

Visual Question Answering Based on Image and Video - Thao Minh Le

The lecture covers a new research on semantically understanding visual scenes, in part based on the papers - "Hierarchical Conditional ...

Integrating Non-monotonic Logical Reasoning and Inductive ...

As a motivating example of a task that requires explainable reasoning and learning, we consider Visual Question Answering in which, given an image of a scene, ...

Integrating Non-monotonic Logical Reasoning and Inductive ...

As a motivating example of a task that requires explainable reasoning and learning, we consider Visual Question Answering in which, given an ...

Integrating Deep Learning and Non-monotonic Logical Reasoning ...

Integrating Deep Learning and Non-monotonic Logical Reasoning for Explainable Visual Question Answering. https://doi.org/10.1007/978-3-030-66412-1_36 ·.

Non-monotonic Logical Reasoning and Deep Learning for ...

State of the art visual question answering (VQA) methods rely heavily on deep network architectures. These methods require a large labeled dataset for ...

An Efficient Visual based Question Answering System using ...

The research study implemented a VQA system that, by using a deep convolution neural network (CNN) that collects image attributes, achieves proper knowledge ...

visual question answering (vqa) using deep learning

Visual Question Answering (VQA) is a research area about building a computer system to answer questions presented in an image and a natural language, ...

Non-monotonic Logical Reasoning and Deep Learning for ...

State of the art visual question answering (VQA) methods rely heavily on deep network architectures. These methods require a large labeled dataset for ...

Linguistic issues behind visual question answering - PMC - NCBI

Boosted by impressive advancements in machine learning, the task of answering visually‐grounded questions has experienced a renewed interest in recent years, to ...

Deep Learning Approach to Visual Question Answering - GitHub

Both of these independent blocks which are Neural network for images i.e CNN and Neural Network for Ques- tions i.e RNN must be integrated in a cohesive manner ...

Visual Question and Answering in Videos Using Deep Learning

Visual Question Answering or VQA uses deep learning, computer vision, and natural language processing techniques. Natural Language Processing is ...

Discover Visual Question Answering (VQA) datasets - Innovatiana

Drawing on deep learning and data annotation techniques, VQA makes it possible to develop models capable of understanding the content of an ...

Research Topics in Visual Question Answering - S-Logix

As an interdisciplinary field, VQA combines computer vision, natural language processing, and machine learning to produce automated systems that can answer ...

Visual Question Answering Using Deep Learning | IJSREM Journal

Visual Question Answering Using Deep Learning ... Abstract – Answers to Practical Questions is a research center on how to build a computer ...

Using Deep Learning to Answer Visual Questions from Blind People

visual question. The design of an VQA models goes beyond simply merging the two modalities. Previous literature illustrates how is possible to integrate ...

Researching Visual Question Answering: Bridging the Gap between ...

The result of the research is a software system for visual question answering, which includes a server with a trained neural network responsible ...

Devi Parikh: Visual Question Answering (VQA)

This is one of the advantages deep learning has over other AI approaches, and it means that systems concerns have renewed importance for modern AI. In this ...

Integrating Non-monotonic Logical Reasoning and Inductive ...

Integrating Non-monotonic Logical Reasoning and Inductive Learning with Deep. Learning for Explainable Visual Question Answering. Mohan Sridharan1 , Heather ...