Results 121 to 130 of about 5,075,844 (278)
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
Single‐Step Analog In‐Memory Matrix Computation in Three‐Dimensional Circuits
A wooden model illustrates a 3D memristive array designed for single‐step kernel convolutions. It shows how two‐dimensional input data are mapped into the 3D array and convolved in parallel with stored kernels. Color‐coded connection points represent programmed memory‐element values, with each color corresponding to a specific kernel weight.
Alireza Jaberi Rad +8 more
wiley +1 more source
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou +5 more
wiley +1 more source
An large language model‐powered multimodal framework is developed for robotic endoscope control. It integrates speech recognition and real‐time instrument tracking, achieving 89.47% command accuracy with ~1s latency for natural human–robot interaction in minimally invasive surgery.
Yisen Huang +7 more
wiley +1 more source
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati +3 more
wiley +1 more source
Explainable human‐in‐the‐loop healthcare image information quality assessment and selection
Abstract Smart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high ...
Yang Li, Sezai Ercisli
wiley +1 more source
AI‐Powered Smart Displays and AR Glasses: Perspectives and Challenges
This perspective examines how AI is reshaping smart displays and AR glasses. The latest in image‐quality enhancement, sensor‐integrated display optimization, and physiological sensing in display systems, followed by AI‐assisted AR technologies including waveguide optimization, image compensation, foveated rendering, and multimodal sensing, is discussed.
Luke Benoit +8 more
wiley +1 more source
An efficient deep learning model for brain tumour detection with privacy preservation
Abstract Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning.
Mujeeb Ur Rehman +8 more
wiley +1 more source
Fast Face Recognition Approach Using a Graphical Processing Unit "GPU"
In this manuscript, we present an implementation of a correlation method for face recognition application on GPU. Our correlator is based on the famous "4f" setup and the use of a Phase Only Filter (POF). Traditionally, the correlation method is implemented using optical components for real-time application.
Ouerhani, Yousri +2 more
openaire +2 more sources
Automatic left ventricular segmentation in echocardiography is critical for cardiac function assessment but remains challenging due to limited crossdomain feature interaction. This paper proposes SFMFNet, a Spatial‐Frequency Multi‐Scale Fusion Network that integrates multiscale convolution, wavelet transform, and Fourier transform.
Dang Li +3 more
wiley +1 more source

