Results 101 to 110 of about 66,359 (302)
The transition to post-quantum cryptography introduces substantial computational overhead that can degrade application performance in datacenter environments, particularly under system contention when there is competition to access shared computational ...
Joseph Meyer +3 more
doaj +1 more source
Task‐adaptive programmable optics enables label‐free virtual staining through optical‐attention‐guided acquisition and reconstruction. By optimizing wavelength, illumination angle, exposure time, and imaging depth, the framework learns task‐relevant optical measurements, generating clinically interpretable virtual stains with improved fidelity, non ...
Tianyue He +13 more
wiley +1 more source
As the exponential growth in advanced compute workloads drives intra-datacenter interconnects to ever increasing bitrates, optical networking equipment has risen to the challenge by shifting from NRZ signaling to bandwidth efficient modulation methods ...
Itamar-Mano Priel +3 more
doaj +1 more source
Facial Expression Recognition With Deep Learning Approach For Detecting Stress
A workplace stress detection system using face images require a low-cost installation and does not interfere with the movements of workers, thus the system will be the better promising approach than physiological data based approach using wearable ...
Sung-Min Park, Wonju Seo, Seunghyun Lee
core
Arterial Blood‐Mediated Deep‐Tissue Photoacoustic Oximetry
The arterial prior method (APM+) for photoacoustic oximetry is introduced, which leverages the high arterial blood oxygenation to calibrate the fluence at the artery and estimate the oxygenation of the surrounding tissue, thus circumventing the spectral coloring problem. APM+’s accuracy and consistency are shown in a series of phantom and in vivo human
Karteekeya Sastry +7 more
wiley +1 more source
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen +5 more
wiley +1 more source
Joint Training on AMD and NVIDIA GPUs
As large language models continue to scale, training demands on compute and system capacity grow rapidly, making single-vendor homogeneous clusters insufficient. This paper presents a technical solution for heterogeneous mixed training in AMD-NVIDIA environments.
Jon Hu +3 more
openaire +2 more sources
Development of prototype based on NVIDIA DIGITS for PyTorch
Deep learning frameworks such as Caffe and Tensorflow has significantly eased the process of creating deep neural networks. However, these frameworks do not come with a built in visual interface which can be difficult to use.
Chen, Benedict Si-Yuan
core
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
We present an efficient tensor-network-based approach for simulating large-scale quantum circuits exemplified by quantum support vector machines (QSVMs).
Kuan-Cheng Chen +8 more
doaj +1 more source

