17 articles
Researchers introduce TomFormer, a transformer-based model for accurate and early detection of tomato leaf diseases, with the goal of deployment on the Hello Stretch robot for real-time diagnosis. TomFormer combines a visual transformer and CNN, achieving state-of-the-art results on KUTomaDATA, PlantDoc, and PlantVillage datasets. KUTomaDATA was collected from a greenhouse in Abu Dhabi, UAE.
The study introduces the Qatar University Dual-Machine Bearing Fault Benchmark dataset (QU-DMBF) containing sound and vibration data from two motors across 1080 conditions. It proposes a deep learning approach for sound-based fault detection, addressing limitations of vibration-based methods. Experiments on QU-DMBF show sound-based detection is more robust, independent of sensor location, and cost-effective while matching vibration-based performance. Why it matters: The new dataset and findings could shift the focus toward sound-based methods for more reliable and accessible predictive maintenance in industrial settings.
Researchers introduce Arabic Mini-ClimateGPT, a tailored Arabic LLM for climate change and sustainability. The model is fine-tuned on the Clima500-Instruct dataset and uses vector embedding retrieval during inference. Evaluations show the model outperforms baseline LLMs and is preferred by experts in 81.6% of cases.
KAUST · · Research Renewable Energy
KAUST researchers found Y-series nonfullerene acceptors enhance the outdoor stability of organic solar cells, enabling energy-efficient windows. They also used satellite data to show managed vegetation can mitigate rising temperatures across Saudi Arabia's agricultural regions. Additionally, they developed DeepKriging, a deep neural network, to solve complex spatiotemporal datasets and tested it on air pollution. Why it matters: This research addresses critical challenges in renewable energy, climate change, and AI data privacy relevant to Saudi Arabia and the broader region.
ClimateCrete, a KAUST spinout, has raised investment for its technology that modifies sand particles to make them suitable for concrete manufacturing. The patented tech reduces the need for cement and lowers CO2 emissions by up to 60 percent. Tests show a significant increase in strength compared to untreated sand. Why it matters: This technology addresses the global shortage of suitable construction sand and supports Saudi Arabia's carbon-neutrality goals by enabling a 100% domestic supply chain for concrete.
KAUST · · Research Healthcare
KAUST · · Research Healthcare
KAUST · · Research Infrastructure
KAUST · · Education Innovation
KAUST · · Healthcare Research
KAUST · · Education Saudi Vision 2030
KAUST · · Research Partnership
KAUST · · Partnership Research
KAUST · · Policy Partnership
KAUST · · Partnership Research