Results 91 to 100 of about 956,220 (295)

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

TRPC3‐Driven Calcium Microdomains Instruct Peripheral Nerve Regeneration With Protective Implications for Central Neurons

Advanced Science, EarlyView.
How localized Ca2+ signals orchestrate neural repair remains unclear. Here, we show that TRPC3‐driven calcium microdomains direct nerve repair by coupling spatially confined Ca2+ signals to axon regeneration. This module operates in injured peripheral neurons and correlates with neuroprotection in Parkinson's disease, revealing a spatial logic for ...
Yu Lu, Jianbo Zhao, Zhenli Xie, Yuan Wang, Ruolin Wang, Bianbian Wang, Chuhan Shen, Yali Chen, Jingyu Yao, Ziyang Li, Huadong Xu, Zuying Chai, Zhuoyu Zhang, Changhe Wang, Rong Huang   +14 more
wiley   +1 more source

Multi-scale CNN-CrossViT network for offline handwritten signature recognition and verification

Complex & Intelligent Systems
Developing technologies that can accurately identify and highlight subtle differences in signatures is crucial for improving the performance of signature recognition and verification.
Wanying Li, Mahpirat Muhammat, Xuebin Xu, Alimjan Aysa, Kurban Ubul   +4 more
doaj   +1 more source

Handwritten Signature Generation Using Denoising Diffusion Probabilistic Models with Auxiliary Classification Processes

Applied Sciences
Automatic signature verification has been widely studied for authentication purposes in real life, but limited data availability still poses a significant challenge.
Dong-Jin Hong, Won-Du Chang, Eui-Young Cha   +2 more
doaj   +1 more source

An offline signature verification technique using pixels intensity levels [PDF]

, 2016
Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb
Khan, M.N.A., Subhan, Fazli, Shah, Asadullah, Fayaz, Muhammad, Shah, Abdul Salam   +4 more
core   +1 more source

AI‐Powered, Temperature‐Resolved Centrifugal Microfluidics for Rapid 3D Phase‐Diagram Generation of Biomolecular Condensates

Advanced Science, EarlyView.
By merging centrifugal microfluidics, precise temperature control, and AI image recognition, T‐PhaseMap transforms biomolecular condensate phase mapping into a rapid, temperature‐resolved workflow. It generates 3D composition–temperature phase diagrams within 30 min, resolves four phase states, and uncovers temperature‐dependent heparin sodium ...
Jiashuo Li, Pengjie Li, Kaiting Zhang, Yongqi Guo, Peng Chen, Bi‐Feng Liu, Yiwei Li   +6 more
wiley   +1 more source

Convolutional Neural Network Based Offline Signature Verification Application

, 2018
One of the most important biometric authentication technique is signature. Nowadays, there are two types of signatures, offline (static) and online (dynamic).
Yapici, Muhammed Mutlu, TOPALOĞLU, NURETTİN, TEKEREK, ADEM   +2 more
core   +1 more source

Vanilla Convolutional Neural Network is all you Need for Online and Offline Signature Verification

International Journal of Applied Mathematics and Computer Science
Recent advances in deep learning have been utilized successively to improve the performance of signature verification (SV) systems. Deep models proposed in the literature are complicated and need to learn many parameters to give acceptable error rates ...
Yilmaz Mustafa Berkay, Öztürk Kağan
doaj   +1 more source

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

Advanced Electronic Materials, EarlyView.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci, P. Mannocci, M. Porzani, D. Bridarolli, F. Carletti, M. Farronato, D. Ielmini   +6 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source