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Image annotation plays an important role in image retrieval process, especially when it comes to content-based image retrieval. In order to compensate the intrinsic weakness of machines in performing cognitive task of (human-like) image annotation, leveraging humans’ knowledge and abilities in the form of crowdsourcing-based annotation have gained momentum. Among various approaches for this purpose, an innovative one is integrating the annotation process into the CAPTCHA workflow. In this paper, the current state of the research works in the field and experimental efficiency analysis of this approach are investigated.

At first, and with the aim of presenting a current state report of research studies in the field, a comprehensive literature review is provided. Then, several experiments and statistical analyses are conducted to investigate how CAPTCHA-based image annotation is reliable, accurate and efficient.

In addition to study of current trends and best practices for CAPTCHA-based image annotation, the experimental results demonstrated that despite some intrinsic limitations on leveraging the CAPTCHA as a crowdsourcing platform, when the challenge, i.e. annotation task, is selected and designed appropriately, the efficiency of CAPTCHA-based image annotation can outperform traditional approaches. Nonetheless, there are several design considerations that should be taken into account when the CAPTCHA is used as an image annotation platform.

To the best of the authors’ knowledge, this is the first study to analyze different aspects of the titular topic through exploration of the literature and experimental investigation. Therefore, it is anticipated that the outcomes of this study can draw a roadmap for not only CAPTCHA-based image annotation but also CAPTCHA-mediated crowdsourcing and even image annotation.

Currently, the evaluation of scientific performance of universities is one of the important indicators in various ranking systems. One way to evaluate the academic performance of universities is to analyze the scientific documents of universities in reputable international databases. The purpose of this article is to analyze and evaluate the scientific publications of Alzahra University (Iran) as the top 100–200 universities during 1986–2019.

This study was performed using bibliometrics and visualization techniques. The Scopus database was used to collect data. Affiliation search and advanced search were used to retrieve the data. Excel, VOSviewer and CRExplorer software were used to analyze the data.

The results showed that the scientific publications and received citations by Alzahra University documents during the time have been upward. At the national level, it was the most scientific collaboration with researchers at the University of Tehran. Also at the international level, the most scientific collaboration has been with the United States, Canada and Germany. In total, 80% of scientific publications were published by 20% of authors. Also, 70% of the highly cited articles were published in journals with quartile 1. Finally, clustering results showed that Alzahra University's scientific publications are in five main categories, including “chemistry,” “physics,” “biology,” “psychology and educational sciences” and “accounting sciences, management, and computer science.”

This study could be a good model for evaluating the performance of scientific productions of universities and scientific institutions with bibliometrics and visualization approaches.