Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...

Abstract: Realizing unified 3D object detection, including both indoor and outdoor scenes, holds great importance in applications like robot navigation. However, involving various scenarios of data to ...

DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...

Weed control is essential in apple orchards because weeds compete with trees for nutrients, water and sunlight, which can ...

As global mobility shifts toward autonomy and electrification, front collision warning systems will evolve into intelligent, constantly learning safety ecosystems. By 2035, FCW will be integrated with ...

Abstract: Object detection is a cornerstone of modern computer vision, driving advances in autonomous driving, robotics, surveillance, and smart infrastructure. However, detection performance and ...

As more nations and private companies turn their sights toward the Moon, the region between Earth and lunar orbit has become a frontier of opportunity, risk, and strategic competition. Now, the U.S.

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN integration. It improves dynamic lesion detection, temporal ...

New Hubble images have revealed objects with shapes and patterns that don’t match any known class of celestial bodies. Scientists expected distant stars and nebulae, not these unusual structures.