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Stefan Depeweg; Contantin A. Rothkopf; Frank Jäkel – Cognitive Science, 2024
More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…
Descriptors: Visual Learning, Problem Solving, Cognitive Science, Artificial Intelligence
Han Zhang; Yilang Peng – Sociological Methods & Research, 2024
Automated image analysis has received increasing attention in social scientific research, yet existing scholarship has mostly covered the application of supervised learning to classify images into predefined categories. This study focuses on the task of unsupervised image clustering, which aims to automatically discover categories from unlabelled…
Descriptors: Social Science Research, Visual Aids, Visual Learning, Cluster Grouping
Chenghao Wang; Xueyun Li – International Journal of Computer-Assisted Language Learning and Teaching, 2025
D-ID Creative Reality Studio (D-ID) is a platform for creating Artificial Intelligence (AI) presenter (digital human) videos, translating videos, and designing conversational agents. D-ID seamlessly integrates deep-learning face animation technology, large language models (LLMs), natural language processing (NLP), and speech synthesis and…
Descriptors: Artificial Intelligence, Design, Video Technology, Animation
Yuchen Chen; Xinli Zhang; Lailin Hu – Educational Technology & Society, 2024
In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate…
Descriptors: Elementary School Students, Grade 5, Poetry, Artificial Intelligence