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The Application of Convolution Neural Networks in Handwritten Numeral Recognition

Xiaofeng Han, Yan Li Li
2015 International Journal of Database Theory and Application  
They have been applied to many image recognition tasks and have attracted the attention of the researchers of many countries in recent years.  ...  Convolutional neural networks are a technology that combines artificial neural networks and recent deep learning methods.  ...  Acknowledgements This work is supported by the National Natural Science Foundations of China(61402265 and 61170054 )  ... 
doi:10.14257/ijdta.2015.8.3.32 fatcat:5t565xg6vze3dkp62prjhehz64

Image Pre-processing on Character Recognition using Neural Networks

Khushbu Khushbu, Sakshi Mehta
2013 International Journal of Computer Applications  
The use of artificial neural network in applications can dramatically simplify the code and improve quality of recognition while achieving good performance.  ...  This paper, presents a theoretical and practical basis of preprocessing on handwritten text for character recognition using forward-feed neural networks.  ...  Back Propagation Algorithm The feed forward network can be applied to a variety of classification and recognition problems.  ... 
doi:10.5120/14175-2165 fatcat:o7bhyxubcfcdvbk5xexa6qv2wi

Novel Optimization of Identified Palm Geometry Using Image Segmentation

Mahalakshmi B. S., Sheela S. V.
2022 International Journal of Online and Biomedical Engineering (iJOE)  
Further proposed system uses machine learning approach (convolution neural network and Siamese Neural Network) to further assist in optimizing the segmentation performance.  ...  a case study of finger recognition.  ...  in order to construct an input mask followed by applying Siamese Neural Network.  ... 
doi:10.3991/ijoe.v18i05.29361 fatcat:dhg7f5vdt5bupes5xaxvmrrx5m

Recognition of Off-Line Hand-Written Alphabets Using Knowledge-Based Computational Intelligence

Muhammad Hasseb, Ghulam Abbas
2019 Pakistan journal of engineering & technology  
A system is proposed to recognize characters using convolutional neural network and is evaluated on a benchmark dataset named as EMNIST to show the performance of the proposed technique.  ...  This work provides such a simplified and accurate method for the recognition of handwritten characters.  ...  NEURAL NETWORKS A. Neural Networks' Background Neural networks try to solve the problem with a different approach inspired from human visual cortex.  ... 
doaj:88f00dccc7a943abb557baaaf3d003d7 fatcat:kanhuncw2nfgho3srmdo6ta3hm

A Bayesian approach for initialization of weights in backpropagation neural net with application to character recognition [article]

Nadir Murru, Rosaria Rossini
2020 arXiv   pre-print
In this paper, an original algorithm for initialization of weights in backpropagation neural net is presented with application to character recognition.  ...  Convergence rate of training algorithms for neural networks is heavily affected by initialization of weights.  ...  Special thanks go to Dott. Tiziana Armano and Prof. Anna Capietto for their support to this work. We would like to thanks the anonymous referees whose suggestions have improved the paper.  ... 
arXiv:2004.01875v1 fatcat:z235l2kzmzhtvpbhgqwnddl4ne

A Bayesian approach for initialization of weights in backpropagation neural net with application to character recognition

Nadir Murru, Rosaria Rossini
2016 Neurocomputing  
In this paper, an original algorithm for initialization of weights in backpropagation neural net is presented with application to character recognition.  ...  Convergence rate of training algorithms for neural networks is heavily affected by initialization of weights.  ...  Since neural nets are applied to many different complex problems, these methods have fluctuating performances.  ... 
doi:10.1016/j.neucom.2016.01.063 fatcat:i5ty5t335rb3paw7giqpuqlmoq

FPGA-based Implementation of Stochastic Configuration Network for Robotic Grasping Recognition

Jiaqi Pan, Feng Luan, Yunqi Gao, Yangjie Wei
2020 IEEE Access  
Compared with the traditional back propagation (BP) neural network [10] , it has better performance in terms of time and accuracy.  ...  Therefore, in some applications that require real-time performance, compared with software-based neural networks, FPGA-based neural networks will have more advantages due to the parallel processing characteristics  ... 
doi:10.1109/access.2020.3012819 fatcat:hti2j6m62jd6hhxd3jwwfpfmcm

Discriminative training for speech recognition

Yoh'ichi Tohkura
1992 Journal of the Acoustical Society of Japan (E)  
The recent advent of artificial neural networks (ANN) and learning vector quantization (LVQ), and their good performance in speech recognition tasks, has revived an interest in the discriminative training  ...  The 1991 IEEE Workshop on Neural Networks for Signal Processing held in Princeton, New Jersey was a good occasion to discuss and recognize the im portance of theoretical advancements in discrimina tive  ...  The resulting ANNs were applied to phoneme recognition with an improvement of recognition performance.  ... 
doi:10.1250/ast.13.331 fatcat:gm65fwyk4bfojlvsf5ltw2c6mi

COMPARATIVE CHARACTERISTICS OF KERAS AND LASAGNE MACHINE LEARNING PACKAGES

V. M. Sineglazov, M. O. Omelchenko, V. P. Hotsyanivskyy
2017 Electronics and Control Systems  
A comparative analysis of the Lasagne and Keras computer libraries has been performed to construct convolutional neural networks used in image processing systems.  ...  The carried out researches have allowed to define their advantages and disadvantages that will allow to make to researchers the correct choice at the decision of applied problems.  ...  A natural analog shows that the set of problems that are not yet subject to the resolution of existing computers, but can be effectively solved by convulated neural networks [1] . II.  ... 
doi:10.18372/1990-5548.53.12151 fatcat:es6ufddqjfa3tnmm3hqxq5mxme

Single neuron-based neural networks are as efficient as dense deep neural networks in binary and multi-class recognition problems [article]

Yassin Khalifa, Justin Hawks, Ervin Sejdic
2019 arXiv   pre-print
By employing three datasets, we test the use of a population of single neuron networks in performing multi-class recognition tasks.  ...  We investigate the ability to model high dimensional recognition problems using single or several neurons networks that are relatively easier to train.  ...  Since over-reduction of network size alone, shows poor performance in multi-class recognition problems as it appears in Fig. 1(g) , simplifying the recognition problem might be the solution.  ... 
arXiv:1905.12135v1 fatcat:qxmnrtzwgfbetabhlgaspdsztq

A Novel Combinational Convolutional Neural Network for Automatic Food-Ingredient Classification

Lili Pan, Cong Li, Samira Pouyanfar, Rongyu Chen, Yan Zhou
2019 Computers Materials & Continua  
With the development of deep learning and Convolutional Neural Networks (CNNs), the accuracy of automatic food recognition based on visual data have significantly improved.  ...  We construct an up-to-date combinational convolutional neural network (CBNet) with a subnet merging technique. Firstly, two different neural networks are utilized for learning interested features.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2020.06508 fatcat:p5kdg736hvcvjjih4zfa6scpsy

Deep Convolutional Neural Network for Recognizing the Images of Text Documents

Vladimir A. Golovko, Aliaksandr Kroshchanka, Egor Mikhno, Myroslav Komar, Anatoliy Sachenko, Sergei V. Bezobrazov, Inna Shylinska
2019 Modern Machine Learning Technologies  
A comparative analysis of various methods and architectures used to solve the problem of object detection is carried out.  ...  A neural network algorithm for labeling images in text documents is developed on the basis of image preprocessing that simplifies the localization of individual parts of a document and the subsequent recognition  ...  The algorithm simplifies the localization of individual parts of a document and the subsequent recognition of localized blocks using a deep convolutional neural network.  ... 
dblp:conf/momlet/GolovkoKMKSBS19 fatcat:mg6vpxpnwncjpckswpondwxgvm

Character Recognition of Vehicle License Plate using Feature Extraction: A Review Paper

Tarun Dagar
2018 International Journal for Research in Applied Science and Engineering Technology  
The License Plate Recognition (LPR) system is the most popular method for the mass surveillance of the automobiles now days.  ...  The LPR system is basically works into 3 steps , 1 st step is to recognize vehicle license plate and then extract numbers from that and third step is to character recognition means to read out the characters  ...  Now a day's , various types of multilayer NN are being applied for the character recognition eg.  ... 
doi:10.22214/ijraset.2018.3514 fatcat:hjxyfd6nk5bijeskyg6eo3pdoy

Residual Learning Based CNN for Gesture Recognition in Robot Interaction

Hua Han
2021 Journal of Information Processing Systems  
Hence, a residual learning neural network based on a deep convolutional neural network is proposed. First, small convolution kernels are used to extract the local details of gesture images.  ...  The complexity of deep learning models affects the real-time performance of gesture recognition, thereby limiting the application of gesture recognition algorithms in actual scenarios.  ...  This network overcomes the problem of excessive deep network parameters to a certain extent and reduces the possibility of gradient dispersion problems.  ... 
doi:10.3745/jips.01.0072 dblp:journals/jips/Han21 fatcat:duqwer27gnfsrcdbzlcdr7kxy4

Automatic Temporal Location and Classification of Human Actions Based on Optical Features

Seyed Ali Etemad, Pierre Payeur, Ali Arya
2009 2009 2nd International Congress on Image and Signal Processing  
neural networks.  ...  This paper presents a method for automatic temporal location and recognition of human actions. The data are obtained from a motion capture system.  ...  ACKNOWLEDGMENT The authors would like acknowledge Paul Slinger for his aid through the course of this research.  ... 
doi:10.1109/cisp.2009.5304683 fatcat:5wxq3yv4qbfnrbxvn5vnhh4wmu
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