Publications by authors named "T S Mahesh"
Atoms in Rydberg states are an important building block for emerging quantum technologies. While excitation to Rydberg orbitals is typically achieved in more than tens of nanoseconds, the physical limit is in fact much faster, at the ten picoseconds level. Here, we tackle such ultrafast Rydberg excitation of a rubidium atom by designing a dedicated pulsed laser system generating 480 nm pulses of 10 ps duration.
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- The classification of brain tumors using medical imaging is crucial for accurate diagnosis but faces challenges due to tumor complexity and the need for precision.
- Existing methods rely on traditional machine learning and deep learning models, which struggle with overfitting from small datasets and have high computational requirements, limiting real-time use.
- This research presents an advanced model based on the Xception architecture, combining transfer learning and customized layers to improve diagnostic performance, achieving 98.039% accuracy and over 96% precision and recall, thereby offering a promising tool for clinical applications.
The early detection and diagnosis of gastrointestinal tract diseases, such as ulcerative colitis, polyps, and esophagitis, are crucial for timely treatment. Traditional imaging techniques often rely on manual interpretation, which is subject to variability and may lack precision. Current methodologies leverage conventional deep learning models that, while effective to an extent, often suffer from overfitting and generalization issues on medical image datasets due to the intricate and subtle variations in disease manifestations.
View Article and Find Full Text PDFRetinal vessel segmentation is a critical task in fundus image analysis, providing essential insights for diagnosing various retinal diseases. In recent years, deep learning (DL) techniques, particularly Generative Adversarial Networks (GANs), have garnered significant attention for their potential to enhance medical image analysis. This paper presents a novel approach for retinal vessel segmentation by harnessing the capabilities of GANs.
View Article and Find Full Text PDFRydberg atoms in optical lattices and tweezers is now a well-established platform for simulating quantum spin systems. However, the role of the atoms' spatial wave function has not been examined in detail experimentally. Here, we show a strong spin-motion coupling emerging from the large variation of the interaction potential over the wave function spread.
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