This process of looking and asking questions about what you are looking at is needed at all levels of science, and science ...

Methods: This study proposed an autoencoder learning ... capacity compared to other approaches. Consequently, its downstream classification ability can be significantly improved, which cannot be done ...

Thus, we use the robustness of deep learning to improve the whole system. We have combined traditional geometry-based approaches to introduce a complete visual SLAM system for monocular, binocular, ...

A streamlined SFT (Supervised Fine-Tuning) and Agent-RL (Reinforcement Learning ... complex visual problems, moving beyond passive observation towards active visual cognition. Current LVLMs excel at ...

Artificial intelligence is playing an increasingly vital role in modern medicine, particularly in interpreting medical images ...

Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

DeepSeek-V3 represents a breakthrough in cost-effective AI development. It demonstrates how smart hardware-software co-design ...

A novel vision sensor inspired by the neural transmission mechanisms of the human brain has been developed to efficiently and accurately extract object outlines even under fluctuating lighting ...

Today, we are witnessing a paradigm shift towards a more modular design approach that disaggregates SoC functions into ...