Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Deep Learning Inspired Nonlinear Classification Methodology for Handwritten Digits Recognition Using DSR Encoder Subject The topic of the resource Adaptive voting scheme; Batch normalization; DDRNet approach; MaxPooling; SqueezeNet Description An account of the resource The overlapped handwritten digit classification is a global challenge and a significant measure to assess the network recognition ability ratio. Most efficient models have been designed based on convolutional neural networks (CNN) for effective image classification and digit identification. Subsequently, multiple CNN models have inadequate accuracy because of high degree parameter dimensions that lead to abnormal digit detection error rates and computation complexity. We propose a Deep Digit Recognition Network (DDRNet) based on Deep ConvNets to minimize the number of parameters and features to keep the model light while maximizing the accuracy with an adaptive voting (AV) scheme for digit recognition. The individual digit is identified by CNN, and uncertain digits or strings are identified by Deep Convolutional Network (DCN) with AV scheme through Voting-Weight Conditional Random Field (VWCRF) strategy. These methods originated with the YOLO algorithm. The simulations show that our DDRNet approach achieves an accuracy of 99.4% without error fluctuations, in a stable state with less than 15 epochs contrast with state-of-art approaches. Additionally, specific convolution techniques (SqueezeNet, batch normalization) and image augmentation techniques (dropout, back-propagation, and an optimum learning rate) were examined to assess the system performance based on MNIST dataset (available at: http://yann.lecun.com/exdb/mnist/). 2022, King Fahd University of Petroleum &amp; Minerals. Creator An entity primarily responsible for making the resource Singh D.; Bano S.; Samanta D.; Mekala M.S.; Islam S.H. Source A related resource from which the described resource is derived Arabian Journal for Science and Engineering, Vol-48, No. 2, pp. 1385-1397. Publisher An entity responsible for making the resource available Institute for Ionics Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s13369-022-06865-8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s13369-022-06865-8</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129021833&amp;doi=10.1007%2Fs13369-022-06865-8&amp;partnerID=40&amp;md5=917fde654f1649e0b911d1d902a384f6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129021833&amp;doi=10.1007%2fs13369-022-06865-8&amp;partnerID=40&amp;md5=917fde654f1649e0b911d1d902a384f6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2193567X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Singh D., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Bano S., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, Vaddeswaram, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Mekala M.S., Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38544, South Korea, RLRC for Autonomous Vehicle Parts and Materials Innovation, Yeungnam University, Gyeongsan, 38544, South Korea; Islam S.H., Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, Kalyani, West Bengal, 741235, India