A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric traits and estimation of yields in both laboratory and field settings without ...

The deep learning field has been dominated by “large models” requiring massive computational resources and energy, leading to unsustainable environmental and economic challenges. To address this, ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

A new forensic framework designed specifically for the Internet of Things (IoT) is discussed in the International Journal of ...

BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...

One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Ultrasound (US) imaging is a widely employed diagnostic tool used for real-time imaging of various organs and tissues using ultrasonic sound waves. The waves are sent into the body, and images are ...