[HTML][HTML] Multiscale feature extraction and fusion of image and text in VQA
Abstract The Visual Question Answering (VQA) system is the process of finding useful
information from images related to the question to answer the question correctly. It can be …
information from images related to the question to answer the question correctly. It can be …
Information fusion for multi-scale data: Survey and challenges
Q Zhang, Y Yang, Y Cheng, G Wang, W Ding, W Wu… - Information …, 2023 - Elsevier
Abstract Information fusion is a useful technique of combining and merging different
information to form a more complete and accurate result. Traditional information fusion …
information to form a more complete and accurate result. Traditional information fusion …
Knowledge distillation for portfolio management using multi-agent reinforcement learning
Many studies have employed reinforcement learning (RL) techniques to successfully create
portfolio strategies in recent years. However, since financial markets are extremely noisy …
portfolio strategies in recent years. However, since financial markets are extremely noisy …
[HTML][HTML] Multivariate solar power time series forecasting using multilevel data fusion and deep neural networks
Accurate forecasting of regional solar photovoltaic power (SPVP) generation is essential for
efficient energy management and planning. Existing approaches have shown the …
efficient energy management and planning. Existing approaches have shown the …
[HTML][HTML] A model validation of robo-advisers for stock investment
A Shiva, BP Kushwaha, B Rishi - Borsa Istanbul Review, 2023 - Elsevier
The study examines the intention of stock investors to adopt robo-advisers (also known as
automated investing services) in financial investment decisions. Using an adapted …
automated investing services) in financial investment decisions. Using an adapted …
Cool: a conjoint perspective on spatio-temporal graph neural network for traffic forecasting
This paper investigates traffic forecasting, which attempts to forecast the future state of traffic
based on historical situations. This problem has received ever-increasing attention in …
based on historical situations. This problem has received ever-increasing attention in …
Multi-level Graph Memory Network Cluster Convolutional Recurrent Network for traffic forecasting
L Sun, W Dai, G Muhammad - Information Fusion, 2024 - Elsevier
Traffic forecasting plays a vital role in the management of urban road networks and the
development of intelligent transportation systems. To effectively capture spatial and temporal …
development of intelligent transportation systems. To effectively capture spatial and temporal …
Counting-based visual question answering with serial cascaded attention deep learning
T MeshuWelde, L Liao - Pattern Recognition, 2023 - Elsevier
The counting-based questions play a major part in Visual Question Answering (VQA), the
most challenging factor is counting the different objects present in the images. Recently …
most challenging factor is counting the different objects present in the images. Recently …
Feature selection and hyperparameters optimization employing a hybrid model based on genetic algorithm and artificial neural network: Forecasting dividend payout …
Among the most crucial factors that should be considered in the fundamental decision-
making processes of companies is dividend policy. All market participants pay close …
making processes of companies is dividend policy. All market participants pay close …
Evolving Knowledge Graph Representation Learning with Multiple Attention Strategies for Citation Recommendation System
The growing number of publications in the field of artificial intelligence highlights the need
for researchers to enhance their efficiency in searching for relevant articles. Most paper …
for researchers to enhance their efficiency in searching for relevant articles. Most paper …