Results 61 to 70 of about 427 (175)

Handwritten text recognition using deep learning techniques: A survey [PDF]

MATEC Web of Conferences
HTR (Handwritten Text Recognition) is the automated process of converting handwritten text into digital text, holding immense value in digitizing historical records and facilitating data entry.
Rakesh S., Kushal Reddy P., Prashanth V., Srinath Reddy K.   +3 more
doaj   +1 more source

Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses

Advanced Electronic Materials, EarlyView.
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol, Nikhil Garg, Matteo Mazza, Yanming Zhang, Elisa Zaccaria, Wooseok Choi, Bert Jan Offrein, Laura Bégon‐Lours   +7 more
wiley   +1 more source

Attention-Based Fully Gated CNN-BGRU for Russian Handwritten Text

Journal of Imaging, 2020
This article considers the task of handwritten text recognition using attention-based encoder–decoder networks trained in the Kazakh and Russian languages.
Abdelrahman Abdallah, Mohamed Hamada, Daniyar Nurseitov   +2 more
doaj   +1 more source

TILPDeep: A Lightweight Deep Learning Technique for Handwritten Transformed Invariant Pashto Text Recognition

IEEE Access, 2023
Pashto is the native language of Afghanistan and one of Pakistan’s most essential and regional languages. The Pashto language has a vast number of native speakers who live in various parts of the world.
Muhammad Shabir, Zahoor Jan, Naveed Islam, Inayat Khan, Gauhar Ali, Mohammed ElAffendi   +5 more
doaj   +1 more source

Best Practices for a Handwritten Text Recognition System

, 2022
Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications. Though deep learning methods provide notable boost in performance concerning text recognition, non-trivial deviation in performance can be detected even when small pre-processing or architectural/optimization elements ...
George Retsinas, Giorgos Sfikas, Basilis Gatos, Christophoros Nikou   +3 more
openaire   +4 more sources

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

Diffusion-Enhanced NAT–BART Vision Language Transformer for Unified Urdu Word Recognition

IEEE Access
Handwritten Urdu text recognition remains a very challenging problem due to the cursive and complex nature of the Nastaliq script. Each writer has a unique style, and there is a severe lack of large, well-labeled datasets. These challenges make Urdu text
Wahid Hussain, Shahbaz Hassan, Isma Ul Hassan, Ahmad Raza Shahid, Asif Naeem, Muhammad Usman Yaseen, Nouman Ashraf   +6 more
doaj   +1 more source

Linear and Programmable Long‐Term Plasticity in PECVD Amorphous SiC Memristors

Advanced Electronic Materials, EarlyView.
Stoichiometry‐engineered PECVD amorphous SiC memristors exhibit highly linear and programmable long‐term synaptic plasticity with a nonlinearity as low as 0.08. By controlling the local bonding environment, stable multilevel conductance updates are achieved, enabling robust neural‐network classification on MNIST and CIFAR‐10 and highlighting amorphous ...
Qin Liu, Omesh Kapur, Bohao Ding, Fangnan Chen, Bingkai Ding, Ruomeng Huang, C. H. Kees de Groot   +6 more
wiley   +1 more source

A Pix2Pix Architecture for Complete Offline Handwritten Text Normalization

Sensors
In the realm of offline handwritten text recognition, numerous normalization algorithms have been developed over the years to serve as preprocessing steps prior to applying automatic recognition models to handwritten text scanned images. These algorithms
Alvaro Barreiro-Garrido, Victoria Ruiz-Parrado, A. Belen Moreno, Jose F. Velez   +3 more
doaj   +1 more source

Self-training for Handwritten Text Line Recognition [PDF]

, 2010
Off-line handwriting recognition deals with the task of automatically recognizing handwritten text from images, for example from scanned sheets of paper. Due to the tremendous variations of writing styles encountered between different individuals, this is a very challenging task. Traditionally, a recognition system is trained by using a large corpus of
Volkmar Frinken, Horst Bunke
openaire   +2 more sources