The digital transformation of modern cities by integrating advanced information,
communication, and computing technologies has marked the epoch of data-driven smart city …

The crop variety yield prediction is widely used to select new varieties and select suitable
planting areas for them, but it still suffers from multiple grand challenges, including sparse …

Most multimodal learning methods assume that all modalities are always available in data.
However, in real-world applications, the assumption is often violated due to privacy …

In this paper, we introduce a deep neural network (DNN) for forecasting the intra‐day solar
irradiance, photovoltaic PV plants, regardless of whether or not they have energy storage …

This study proposes a modified gaps filling method, expanding the column mean imputation
method and evaluated using randomly generated missing values comprising 5%, 10 …

The digital transformation of modern cities by integrating advanced information,
communication, and computing technologies has marked the epoch of data-driven smart city …

Reliability and cost are two primary considerations for profiling population-scale prevalence
(PPP) of multiple non-communicable diseases (NCDs). In this paper, we exploit intra …

Online continual learning (OCL) involves deep neural networks retaining knowledge from
old data while adapting to new data, which is accessible only once. A critical challenge in …

Population health monitoring and modelling is important and fundamental for public health
operations for the control and intervention of Non-Communicable Diseases (NCD) …

From early uses to classify handwritten digits [2] to more recent successes in classifying
wider ranges of objects [3], Convolutional Neural Networks (CNNs) have been found to be …