Continuous, real-time monitoring of psychological stress is becoming increasingly important in digital health and remote patient-monitoring systems. However, deploying always-on stress-monitoring models on consumer wearable devices remains challenging because of their limited computational resources and microjoule-...
M. Sajid, N. Aburaed, R. Maskeliūnas· Scientific Reports· 0 citations
Continuous stress monitoring on wrist-worn devices matters for real-time affective computing, digital health, and personalized well-being, yet it remains difficult because a wearable model must operate with few sensors, little compute, and a tight energy budget. Chest-mounted systems can draw on high signal-to-nois...
M. Sajid, N. Aburaed, R. Maskeliūnas· Scientific Reports· 0 citations
A hybrid deep learning framework that couples ConvMixer, for localized lesionscale feature extraction, with a Vision Transformer, for modeling long-range spatial dependencies, and offers a transferable foundation that could be extended toward scalable, environment-robust plant-disease monitoring in other crops and agri...
A. Sharif, Mudassir Khalil, M. Sajid et al.· Frontiers in Plant Science· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
