This study focuses on the classification of six different macrofungi species using advanced deep learning techniques. Fungi species, such as Amanita pantherina, Boletus edulis, Cantharellus cibarius, Lactarius deliciosus, Pleurotus ostreatus and Tricholoma terreum were chosen based on their ecological importance and distinct morphological characteristics. The research employed 5 different machine learning techniques and 12 deep learning models, including DenseNet121, MobileNetV2, ConvNeXt, EfficientNet, and swin transformers, to evaluate their performance in identifying fungi from images. The DenseNet121 model demonstrated the highest accuracy (92%) and AUC score (95%), making it the most effective in distinguishing between species. The study also revealed that transformer-based models, particularly the swin transformer, were less effective, suggesting room for improvement in their application to this task. Further advancements in macrofungi classification could be achieved by expanding datasets, incorporating additional data types such as biochemical, electron microscopy, and RNA/DNA sequences, and using ensemble methods to enhance model performance. The findings contribute valuable insights into both the use of deep learning for biodiversity research and the ecological conservation of macrofungi species.

Turkey’s Corona Precaution Application, a web-based and mobile service, has been actively used by the citizens of the Republic of Turkey and foreigners coming to Turkey since March 19, 2020. This article examines the Corona Precaution Application in terms of its success in detecting risky and positive cases among users. In this informative process analysis study, which is conducted in the lights of Ministry of Health of Turkey data, the efficiency of Corona Precaution Application in March 2020-August 2020 has been measured through the usage statistics from specific provinces and the effect of the application has been proved. The application was used by a total of 2.159.903 people on mobile and web platforms and risk assessments were made. As a result, 135.277 people who were scored as high risk were referred to health-care facilities, and 12.067 people were hospitalized with a positive diagnosis of COVID-19 in PCR tests or isolated at home. When evaluated cumulatively, Corona Precaution Application is used as an effective tool of the health system in the fight against COVID-19. 12.067 people were found to be positive with the referrals to the healthcare facility made through the application; thus, it has been one of the most effective tools in controlling the spread of the disease.