An empirical evaluation of extreme learning machine: application to handwritten character recognition
Extreme learning machine (ELM), a randomized learning paradigm for single hidden layer
feed-forward network, has gained significant attention for solving problems in diverse …
feed-forward network, has gained significant attention for solving problems in diverse …
MJCN: Multi-objective Jaya Convolutional Network for handwritten optical character recognition
In recent years, the non-handcrafted feature extraction methods have gained increasing
popularity for solving pattern classification tasks due to their inherent ability to extract robust …
popularity for solving pattern classification tasks due to their inherent ability to extract robust …
Offline handwritten numeral recognition using convolution neural network
In this current digital age of world, character recognition (CR) has been done through
various machine learning algorithms. And it considered to be one the most challenging …
various machine learning algorithms. And it considered to be one the most challenging …
[HTML][HTML] Accurate recognition of the reproductive development status and prediction of oviposition fecundity in Spodoptera frugiperda (Lepidoptera: Noctuidae) based …
CY Lü, SS Ge, HE Wei, HW Zhang, XM Yang… - Journal of Integrative …, 2023 - Elsevier
Abstract Spodoptera frugiperda (Lepidoptera: Noctuidae) is an important migratory
agricultural pest worldwide, which has invaded many countries in the Old World since 2016 …
agricultural pest worldwide, which has invaded many countries in the Old World since 2016 …
An ensemble method of feature selection and classification of Odia characters
Offline Handwritten Character Recognition of Odia scripts have drawn remarkable attention
by researchers. In the area of Pattern recognition, most challenging task is to classify and …
by researchers. In the area of Pattern recognition, most challenging task is to classify and …
A deep convolutional neural network-based approach for handwritten recognition system
Handwritten recognition model characters have been reported by various researchers in
past years and it becomes the most challenging day by day in this age of the digital world …
past years and it becomes the most challenging day by day in this age of the digital world …
An intelligent college English level 4 pass rate forecasting model using machine learning
Y Chen - Soft Computing, 2023 - Springer
In the last few decades, technological improvements have had a considerable impact on
education, much like many other fields of society and human endeavor. The applications of …
education, much like many other fields of society and human endeavor. The applications of …
Development of a benchmark odia handwritten character database for an efficient offline handwritten character recognition with a chronological survey
R Dey, RC Balabantaray - ACM Transactions on Asian and Low …, 2023 - dl.acm.org
A good benchmark dataset is a primary requirement in the offline handwritten character
recognition (HCR) process. Only three handwritten numerals and alphabet datasets from …
recognition (HCR) process. Only three handwritten numerals and alphabet datasets from …
Intelligent recognition of noun phrases by the integration of Internet of Things and linguistic features
Y Xiao - International Journal of System Assurance Engineering …, 2023 - Springer
This study aims to enhance language comprehension and interaction and foster the
advancement of Chinese information processing technology in the domains of …
advancement of Chinese information processing technology in the domains of …
Discrete cosine transformation based approach for offline handwritten character and numeral recognition
Abstract Handwritten Character Recognition (HCR) of Indic scripts is one of the most
challenging as compared other scripts. Recognition of handwritten character is more difficult …
challenging as compared other scripts. Recognition of handwritten character is more difficult …