Results 101 to 110 of about 6,849,681 (296)
FCN4Flare: fully convolution neural networks for flare detection
ABSTRACT Stellar flares offer invaluable insights into stellar magnetic activity and exoplanetary environments. Automated flare detection enables exploiting vast photometric data sets from missions like Kepler. This paper presents FCN4Flare, a deep learning approach using fully convolutional networks (FCN) for precise point-to-point ...
Minghui Jia, A-Li Luo, Bo Qiu
openaire +2 more sources
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
A brain tumor identification using convolution neural network and fully convolution neural network
Brain tumor identification, along with an investigation, is harmful to the patient. Segmentation, therefore, of paying attention to near-neighborhood growth remains accurate, effective, and healthy. Fully Convolution Neural Network (FCNN) is a reliable picture model to capitulate the hide quality.
Mruthyunjaya, Mandala Suresh Kumar
openaire +2 more sources
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Malaria parasite segmentation using U-Net: Comparative study of loss functions
The convolutional neural network is commonly used for classification. However, convolutional networks can also be used for semantic segmentation using the fully convolutional network approach.
Julisa Bana Abraham
doaj +1 more source
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
We studied the applicability of point clouds derived from tri-stereo satellite imagery for semantic segmentation for generalized sparse convolutional neural networks by the example of an Austrian study area.
Stefan Bachhofner +10 more
doaj +1 more source
Low Frequency Ultrasonic Voice Activity Detection using Convolutional Neural Networks [PDF]
Low frequency ultrasonic mouth state detection uses reflected audio chirps from the face in the region of the mouth to determine lip state, whether open, closed or partially open.
Song, Yan, McLoughlin, Ian Vince
core
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source

