- Integrating deep learning for visual question answering in ...🔍
- A Deep Learning Approach to Visual Question Answering🔍
- Automated construction safety reporting system integrating deep ...🔍
- Understanding Visual Question Answering 🔍
- Visual Question Answering using Deep Learning🔍
- [1909.01860] Visual Question Answering using Deep Learning🔍
- Visual Question Answering Using Deep Learning🔍
- A Deep Learning|Based Bengali Visual Question Answering System ...🔍
Integrating deep learning for visual question answering in ...
Integrating deep learning for visual question answering in ... - Nature
Visual Question Answering (VQA) combines computer vision and natural language processing domains, enabling systems to answer questions about the ...
A Deep Learning Approach to Visual Question Answering - ar5iv
We propose a Deep Learning approach to the visual question answering task, where machines answer to questions about real-world images. By combining latest ...
Automated construction safety reporting system integrating deep ...
Compared to the original YOLOv8n network, the mAP value is improved by 5.1%, while the model parameters and size are significantly reduced. Further, the visual ...
Understanding Visual Question Answering (VQA) in 2025 - viso.ai
With the advancement of Deep Learning (DL), the invention of Visual Question Answering (VQA) has become possible. VQA has recently become popular among the ...
Visual Question Answering using Deep Learning - IJRTI
... visual and textual data is forcing a convergence of efforts from both domains. A lucrative strategy is to integrate CNNs (Convolutional Neural Networks) trained.
[1909.01860] Visual Question Answering using Deep Learning - ar5iv
The advancements in the field of deep learning have certainly helped to develop systems for the task of Image Question Answering. Krizhevsky et al [14] proposed ...
Visual Question Answering Using Deep Learning: A Survey and ...
... Taking advantage of the remarkable advancement of computer vision and natural language processing, due to Deep Neural Networks, several research works have ...
A Deep Learning-Based Bengali Visual Question Answering System ...
Abstract: Visual Question Answering (VQA) is an interdis-ciplinary research area that uses image recognition, natural language processing, and cognitive ...
Multimodal Integration of Human-Like Attention in Visual Question ...
By aiming to integrate human data into and neural attention layers of deep learning ... tion Answering: Do Humans and Deep Networks Look at the Same ...
Visual Question Answering: Bridging the Gap Between Vision and ...
Extracting Features from the Image: - A Convolutional Neural Network (CNN) pre-trained on image datasets like ImageNet is commonly used. - The ...
The multi-modal fusion in visual question answering
Lu et al. (2018a) proposed a new deep neural network for VQA, which integrates two attention mechanisms. The multi-mode multiplicative feature ...
Show Why the Answer is Correct! Towards Explainable AI using ...
We incorporate compositional temporal attention to these deep learning based modules to increase compositionality exploitation. This results in achieving ...
[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 ...
Research On Visual Question Answering Based On Deep Stacked ...
Aiming at the problem that the existing visual question answering model has a language bias in high-level logical reasoning, the model describes images or ...
A Review of Recent Advances in Visual Question Answering
This article aims to explore the untapped possibilities of multimodal deep learning in Visual Question Answering (VQA) and address a research ...
Visual Question Answering - SJSU ScholarWorks
A number of systems have been proposed for VQA that use deep-learning architectures and learning algorithms. This project introduces a VQA system that gains ...
Visual Question Answering Deep Learning | Restackio
VQA systems typically utilize convolutional neural networks (CNNs) to extract features from images and recurrent neural networks (RNNs) or ...
Integrating Deep Learning and Non-monotonic Logical Reasoning ...
In the context of answering explanatory questions about scenes and an underlying classification task, our architecture uses non-monotonic ...
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 ...
Integrating Deep Learning and Non-monotonic Logical Reasoning ...
In this paper, we consider Visual Question Answering (VQA) as a motivating example of a complex task requiring explainable reasoning and learning.