Interdisciplinary studies involving the visual system, computational models and computer vison, show great potential in promoting the joint development of these fields. The achievements and knowledge ...

Very few executives understand the range of digital business models or how the models work. They also don’t understand the range of enabling algorithms or how they work. They therefore cannot ...

The exercises cover a wide variety of data structures and algorithms including DFS and BFS, graphs, linked lists, heaps, dynamic programming, tries, and much more. This book is an excellent ...

This paper presents VARK (Visual, Aural, Reading or Write and Kinesthetic) model as an effective learning style. The learning model is applied in the Data structures and algorithms course. Data ...

1. Explain why categorization-trained deep neural networks cannot model how humans develop their visual system. 2. Describe how contrastive learning algorithms train the neural network models from ...

This project focuses on developing Visual Question Answering (VQA) systems using two models: CLIP (Contrastive Language-Image Pretraining) and BLIP (Bootstrapped Language-Image Pretraining). The goal ...

The field of remote sensing image applications is experiencing unprecedented attention, particularly with the emerging rise of visual question answering (VQA) tasks for remote sensing images. However, ...

When it comes to 3D models, AI algorithms could provide a big help by slashing the ... LRM can take both "normal" images and visual patchworks generated by AI services like DALL-E and Stable ...

The Research Topic on “Integrating Visual System Mechanisms, Computational Models and Algorithms/Technologies” collects novel studies that display a strong synergy between three entities: (1) the ...