In agriculture, many types of weeds have a harmful impact on agricultural productivity.
Recognizing weeds and understanding the threat they pose to farmlands is a significant challenge …

Graph convolutional neural networks (GCNNs) have been successfully applied to a wide
range of problems, including low-dimensional Euclidean structural domains representing …

The study aims to examine the determinants affecting the adoption of e government services
in Vietnam. An extended version of the unified theory of acceptance and use of technology …

Data augmentation (DA) is a universal technique to reduce overfitting and improve the
robustness of machine learning models by increasing the quantity and variety of the training …

With a production of 39 million metric tons each year, rice is one of the main agricultural
products of Vietnam. Thus, rice straw is a significant by-product, whose use in a biorefinery …

… (Jin Lee and Dang Thanh Vu contributed equally to this work.) … DANG THANH VU received
the BS degree in mathematics and computer science from Ho Chi Minh University of Science, …

Capsule networks exhibit the potential to enhance computer vision tasks through their
utilization of equivariance for capturing spatial relationships. However, the broader adoption of …

In the face of increasing irregular temperature patterns and climate shifts, the need for
accurate power consumption prediction is becoming increasingly important to ensure a steady …

Utilizing pre-trained models involves fully or partially using pre-trained parameters as
initialization. In general, configuring a pre-trained model demands practitioners’ knowledge about …

Forecasting, commonly used in econometrics, meteorology, or energy consumption prediction,
is the field of study that deals with time series data to predict future trends. Former studies …