Results 231 to 240 of about 4,718,784 (295)

Searching for effective preprocessing method and CNN based architecture with efficient channel attention on speech emotion recognition. [PDF]

Sci Rep
Kim B, Kwon Y.
europepmc   +1 more source

Fully Additive Vertical Organic Electrochemical Transistors on Renewable and Compostable Substrates Enable Ultrasensitive Bioelectronics

Advanced Functional Materials, EarlyView.
Fully additive vertical organic electrochemical transistors (vOECTs) with channel‐length of 226 nm on a 50 µm compostable substrate achieve >106 current modulation and ∼36 mS transconductance. Ion‐selective integration enables 1.1 mA dec−1 sensitivity and 36 µm detection limit, highlighting a scalable platform for sustainable electronics and ...
Giulia Frusconi, Samuele Lavelli, Zsolt M. Kovács‐Vajna, Fabrizio Torricelli   +3 more
wiley   +1 more source

Lightweight Convolutional Neural Network with Efficient Channel Attention Mechanism for Real-Time Facial Emotion Recognition in Embedded Systems. [PDF]

Sensors (Basel)
Ramirez-Quintana JA, Muñoz-Pacheco JJ, Ramirez-Alonso G, Medrano-Hermosillo JA, Corral-Saenz AD.   +4 more
europepmc   +1 more source

Achieving High ON State Current through Ferroelectric Polarization‐Dependent Interfacial Resistance Switching in Undoped Orthorhombic HfO2 Films

Advanced Functional Materials, EarlyView.
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand, Nuno Estrócio, Ji S. Kim, Babak Bakhit, Marian C. Istrate, Corneliu Ghica, Tiago Rebelo, Nives Strkalj, Abin Varghese, Bernardo Almeida, Luís S. Marques, Bipin Rajendran, Judith L. MacManus‐Driscoll, José P. B. Silva   +13 more
wiley   +1 more source

The application of channel attention mechanism for fusion of painting and live-action footage under deep learning and animation generation technology. [PDF]

Sci Rep
Zhu W, Zhou M.
europepmc   +1 more source

Advances in Sustainable and Wearable Textile Based Soft Robotics

Advanced Functional Materials, EarlyView.
This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas, Marzia Dulal, Sophia K. Novoselov, Victoria K. Novoselov, Kostya S. Novoselov, Shaila Afroj, Nazmul Karim   +6 more
wiley   +1 more source

TDNN achitecture with efficient channel attention and improved residual blocks for accurate speaker recognition. [PDF]

Sci Rep
Li W, Yao S, Wan B, Xiao L, Hou C, Zhong Y, Zhou W.   +6 more
europepmc   +1 more source

Electrospun Wood‐Derived Biopolymers as Electrodes in Electrochemical Energy Storage Technologies

Advanced Functional Materials, EarlyView.
Electrospinning transforms wood‐derived cellulose and lignin into architecturally defined, binder‐free carbon electrodes with tuneable porosity and functionality. This review shows how fibre design enables decoupled charge and mass transport, enhancing performance across battery systems, while identifying key challenges in spinnability, scalability ...
Michael W. Thielke, Hattie R. Chisnall, Jesus Vazquez Chavez, Ana B. Jorge Sobrido   +3 more
wiley   +1 more source

Automatic Removal of Physiological Artifacts in OPM-MEG: A Framework of Channel Attention Mechanism Based on Magnetic Reference Signal. [PDF]

Biosensors (Basel)
Li Y, Wang D, Lu H, Ma Y, Wang C, Su B, Yang J, Cao F, Ning X.   +8 more
europepmc   +1 more source

Implantable Ionic Memristors Based on Natural Polymer Heterojunctions

Advanced Functional Materials, EarlyView.
We report an implantable natural polymer‐based ionic memristor composed of hyaluronic acid, chitosan, and PDMS. The device achieved 98.94% accuracy in MNIST classification while reducing training time by 36.8% compared with a conventional artificial neural network (ANN).
Dong‐yup Lee, Byung Ik Park, Gihyeon Yim, Hyunjae Yoo, Sangjun Ma, Jundong Park, Jeong‐Yun Sun   +6 more
wiley   +1 more source