Deep Learning (DL) has been described as one of the key subfields of Artificial Intelligence
(AI) that is transforming weed detection for site-specific weed management (SSWM). In the …

Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …

Addressing real-world challenges in battery diagnostics, particularly under incomplete or
inconsistent boundary conditions, has proven difficult with traditional methodologies such as …

The importance of biomaterials lies in their fundamental roles in medical applications such
as tissue engineering, drug delivery, implantable devices, and radiological phantoms, with …

This study introduces a methodology tailored to analog hardware architecture for
implementing an artificial neural network. The fundamental components of the architecture …

Streaming data are present all around us. From traditional radio systems streaming audio to
today's connected end-user devices constantly sending information or accessing services …

Abstract Artificial General Intelligence (AGI) is set to profoundly impact the traditional
upstream geoenergy industry (ie, oil and gas industry) by introducing unprecedented …

The exponential growth of the training dataset and the size of the large language model
(LLM) significantly outpaces the incremental memory capacity increase in the graphics pro …

Compositionality can be considered as finding (or creating) the correct meaning of the
constituents of a non-simple language expression or visual image. The Causal Cognitive …

The integration of deep learning (DL) into image processing has driven transformative
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …