The Ichthyological Society of Singapore (ISS) launched the SGFish app on the Apple App Store, which was developed by BSc (Software Engineering) student Brian Sng. The app can identify more than 900 species using an image recognition model. To build the app’s computer vision model, Brian collated and vetted more than 90,000 photos of fish species found near Singapore and neighbouring waters. These were sourced from international databases, society members and his own photos. He said it took two months to train the model with his dataset until it reached an 82.7% accuracy rate. He noted that it is more accurate than the model created by the US-based flora and fauna database iNaturalist, which has an accuracy rate of about 80% for fish across the world. As the community logs more observations, ISS co-founder and SMU student Andriel Cheong hopes the database built from these records can inform environmental impact assessments, giving the authorities a clearer picture of marine biodiversity when planning coastal developments. Beyond recreational fishing and divers, the team hopes the public will use the app to learn about fishes.