Results 41 to 50 of about 815,840 (218)

Handwritten Amharic Word Recognition With Additive Attention Mechanism

IEEE Access
Amharic stands as the second most widely spoken Semitic language globally, trailing only Arabic. As a result, it is a highly resourceful language for hardcopy-document collection, and automatic recognition technology is required.
Ruchika Malhotra, Maru Tesfaye Addis
doaj   +1 more source

Handwritten Geez Digit Recognition Using Deep Learning

Applied Computational Intelligence and Soft Computing, 2022
Amharic language is the second most spoken language in the Semitic family after Arabic. In Ethiopia and neighboring countries more than 100 million people speak the Amharic language.
Mukerem Ali Nur, Mesfin Abebe, Rajesh Sharma Rajendran   +2 more
doaj   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Offline handwritten pre-segmented character recognition of Gurmukhi script

Machine Graphics & Vision, 2016
In this paper, we have proposed a feature extraction technique for recognition of segmented handwritten characters of Gurmukhi script. The experiments have been performed with 7000 specimens of segmented offline handwritten Gurmukhi characters collected ...
Munish Kumar, Manish Jindal, Simpel Jindal, Rajendra Sharma   +3 more
doaj   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

Robust Stitching Interface and Deep Learning Empowered Hydrogel Human‐Machine Interface

Advanced Science, EarlyView.
A molecular design strategy is presented that exploits synergistic carboxylate anion–quaternary ammonium interactions to simultaneously strengthen the hydrogel–PET interface and the bulk hydrogel network. Integrated with deep learning signal processing, the stable hydrogel–PET interface enables consistent signal acquisition and reliable human‐machine ...
Hao Dong, Yiming Luo, Chuanliu Liu, Mahamood Modupe Rasheedat, Wenjiayi Tan, Fangyu Zhao, Yixue Zhang, Chris Connor, Hua Hou, Hamdy Khamees Thabet, Ben Bin Xu, Huige Wei   +11 more
wiley   +1 more source

Machine Learning Approach for Arabic Handwritten Recognition

Applied Sciences
Text recognition is an important area of the pattern recognition field. Natural language processing (NLP) and pattern recognition have been utilized efficiently in script recognition.
A. M. Mutawa, Mohammad Y. Allaho, Monirah Al-Hajeri   +2 more
doaj   +1 more source

Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition [PDF]

E3S Web of Conferences
Analyzing and classifying images of Arabic handwritten characters is crucial for text understanding and interpretation from image data. The recognition of handwritten Arabic characters not only preserves the integrity of the Arabic language but also ...
El Ibrahimi Aissam, Elzaar Abdellah, El Akchioui Nabil, Benaya Nabil, El Allati Abderrahim   +4 more
doaj   +1 more source

A NEW HYBRID SYSTEM FOR RECOGNITION OF HANDWRITTEN-SCRIPT

International Journal of Computing, 2014
A new method for object recognition and classification is presented in this paper. It merges two well-known and tested methods: neural networks and method of minimal eigenvalues. Each of these methods answers for a different part of recognition process. Method of minimal eigenvalues makes preparatory stage of analysis – of coordinates of characteristic
Khalid Saeed 0001, Marek Tabedzki
openaire   +2 more sources

Solution‐Processed Multi‐Junction Optoelectronic Synapses for Mode‐Switchable SWIR Neuromorphic Vision Sensing

Advanced Science, EarlyView.
A novel bias‐programmable shortwave infrared (SWIR) vision sensor is developed using multi‐junction colloidal quantum dots (QDs). Under varying applied voltage, the back‐to‐back rectifying junctions effectively tune trapping centers to switch the device between high‐speed photodetector and persistent synapse modes.
Zhuoyang He, Dae Yang Oh, Yi Ji, Yanyan Li, Chengwei Shan, Soong Ju Oh, Tianshuo Zhao   +6 more
wiley   +1 more source