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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Alzubaidi, Laith H.; Rajendiran, M.; Sattar, Khalid Nazim Abdul; David, Leo Gertrude; Pani, Alok Kumar Title A name given to the resource License Plate Recognition Model based on Improved YOLOv5 and Convolutional LSTM Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 4th IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICDCECE65353.2025.11035571" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDCECE65353.2025.11035571</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105009596382?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105009596382?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Alzubaidi L.H., The Islamic University, Department Computer's Techniques Engineering, Najaf, Iraq; Rajendiran M., Qis College of Engineering and Technology, Department of Computer Science and Engineering, Ongole, India; Sattar K.N.A., Majmaah University, College of Science, Department of Csi, Al Majmaah, Saudi Arabia; David L.G., Kumaraguru College of Liberal Arts and Science, Department of Visual Communication, Coimbatore, India; Pani A.K., Christ (Deemed to be University), Department of Computer Science and Engineering, Bangalore, India Description An account of the resource An end-to-end deep learning model is proposed in this research, for licence plate recognition (LPR) and identification in natural circumstances, which addresses the accuracy and speed limitations of standard licence plate recognition approaches. By adding a better channel attention mechanism and including position data in the output, the proposed method improves the You Only Look Once (YOLOv5) down sampling process and reduces information loss during sampling for better feature extraction. An optimised the YOLO layer is used for single-class recognition to improve efficiency and accuracy. Additionally, Convolutional Long Short-Term Memory (ConvLSTM) combined with Connectionist Temporal Softmax (CTS) is used for character segmentation-free recognition. The utilization of an optimized YOLO layer for single-class recognition enhances both efficiency and accuracy. The integration of ConvLSTM in conjunction with CTS proves to be a breakthrough, facilitating faster convergence, reduced training time, and increase the precision of the model. This configuration speeds up convergence, lowers training time, and increases identification accuracy. The experimental results demonstrate average recognition precision of 99.24% and also robustness, especially in complex situations, with better performance than conventional algorithms. 2025 IEEE. Subject The topic of the resource and licence plate recognition; attention mechanism; connectionist temporal softmax; convolutional long short-term memory; deep learning Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153366-3; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online