[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124746-en":3,"doc-seo-124746-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124746,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",6,"Technology","CAPTCHA recognition using machine learning algorithms with various techniques - research paper","Research focuses on recognizing text-based CAPTCHA tests using advanced machine learning algorithms, emphasizing the security role of CAPTCHAs against automated access. A Convolutional Neural Network (CNN) serves as the base model, and performance is improved through an integrated pipeline. Hyperparameters are tuned via Grid Search Cross-Validation (Grid Search CV) to obtain an optimal configuration. An Ensemble Voting Method then aggregates predictions from multiple CNNs built with those optimized parameters. Results are validated across multiple learning sessions under varied recognition scenarios.","CAPTCHA recognition using machine learning algorithms with various techniques  \nÁdám Kovácsab, Tibor Tajtia  \naEszterházy Károly Catholic University  \n[kovacs2.adam@uni-eszterhazy.hu](kovacs2.adam@uni-eszterhazy.hu)  \n[tajti.tibor@uni-eszterhazy.hu](tajti.tibor@uni-eszterhazy.hu)  \nb University of Debrecen, Doctoral School of Informatics  \nAbstract. In this paper, we present research results on the recognition of text-based CAPTCHA tests using advanced machine learning algorithms and techniques. Text-based CAPTCHAs serve as a crucial security measure to prevent automated access to various web services, but their effectiveness depends on their resistance to sophisticated recognition techniques. To this end, we focus on evaluating and enhancing the performance of recognition models using a Convolutional Neural Network (CNN) as the base model. We propose an integrated approach, which incorporates a systematic parameter optimization strategy using Grid Search Cross-Validation (Grid Search CV) and the Ensemble Voting Method to improve the performance of the recognition model. The use of Grid Search CV enables us to fine-tune the hyperparameters of the CNN model, leading to an optimal configuration.  \nFurther, we investigate the effectiveness of the Ensemble Voting Method to aggregate the predictions from multiple CNN models, each with a set of the optimal parameters obtained from the Grid Search CV. The methods’ performance was evaluated through multiple learning sessions, assessing their effectiveness in recognizing text-based CAPTCHAs under various scenarios.  \nKeywords: Machine learning, CAPTCHA recognition, neural networks, hyperparameter optimization, ensemble methods  \n1. Introduction  \nCAPTCHA, or Completely Automated Public Turing Test to tell Computers and Humans Apart, is a widely used security measure designed to differentiate between  \nSubmitted: August 31, 2023  \nAccepted: November 9, 2023  \nPublished online: November 10, 2023  \nhuman and machine users [18] . However, with recent advancements in artificial intelligence, traditional CAPTCHAs are becoming increasingly susceptible to automated system bypassing.  \nConvolutional Neural Networks (CNNs) are a category of deep learning algorithms that are generally used for processing and analyzing visual data, such as images and videos. Their distinctive architecture leverages spatial hierarchies and local patterns within the data, enabling the automatic learning of complex and abstract features. While CNNs are highly applicable to a range of computer vision tasks, including image recognition, object detection, and segmentation, they can also be employed in other domains, such as time series prediction and speech recognition. The use of CNNs to recognize distorted characters has exposed the vulnerability of existing CAPTCHA systems, emphasizing the need for more sophisticated and resilient alternatives [7] .  \nGrid Search Cross-Validation (Grid Search CV) is a hyperparameter optimization technique in machine learning models [9] . The use of Grid Search CV entails a comprehensive search across a defined range of hyperparameter values, with the performance of each combination assessed via cross-validation (CV) . This approach aids in determining the optimal set of hyperparameters, resulting in superior model performance. Grid Search CV is crucial for developing robust models, as it ensures that they are fine-tuned and capable of generalizing effectively to unseen data.  \nEnsemble methods comprise a collection of powerful machine learning techniques that focus on integrating multiple models to achieve enhanced predictive performance compared to individual models. The core concept underlying ensemble methods are to exploit diversity among various models, which assists in reducing prediction errors, increasing stability, and bolstering generalization capabilities. By aggregating the predictions of several models, ensemble methods can counterbalance the limitations of individual mo","cbCaiiSIXGBHAOHA","https://ap.wps.com/l/cbCaiiSIXGBHAOHA","pdf",644178,1,11,"English","en",105,"# Introduction\n## Dataset\n## Model\n## Voting method","[{\"question\":\"What problem does the paper address?\",\"answer\":\"The paper studies recognizing text-based CAPTCHA tests and evaluates how to improve model performance against distorted and noisy CAPTCHA images.\"},{\"question\":\"How is the CNN model improved?\",\"answer\":\"Hyperparameters of the CNN are optimized using Grid Search Cross-Validation (Grid Search CV) to find an optimal configuration.\"},{\"question\":\"What role does ensemble voting play?\",\"answer\":\"The Ensemble Voting Method combines predictions from multiple CNN models, each using parameters selected by Grid Search CV, to achieve more accurate and robust recognition.\"}]","CAPTCHA recognition using machine learning algorithms with various techniques - research paper | PDF",1785894266,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"captcha-recognition-using-machine-learning-algorithms-with-various-techniques-research-paper","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/captcha-recognition-using-machine-learning-algorithms-with-various-techniques-research-paper/124746/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the paper address?","Question",{"text":75,"@type":76},"The paper studies recognizing text-based CAPTCHA tests and evaluates how to improve model performance against distorted and noisy CAPTCHA images.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the CNN model improved?",{"text":80,"@type":76},"Hyperparameters of the CNN are optimized using Grid Search Cross-Validation (Grid Search CV) to find an optimal configuration.",{"name":82,"@type":73,"acceptedAnswer":83},"What role does ensemble voting play?",{"text":84,"@type":76},"The Ensemble Voting Method combines predictions from multiple CNN models, each using parameters selected by Grid Search CV, to achieve more accurate and robust recognition.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,113,118,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":111,"slug":112},50,"technology",{"id":114,"doc_module":4,"doc_module_name":46,"category_name":115,"show_sort_weight":116,"slug":117},7,"Healthcare",40,"healthcare",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},8,"Research & Report",30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]