Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...
Alphabet’s Intrinsic robotics unit moves into Google, linking DeepMind, Gemini, and Cloud to speed physical AI deployments in factories and logistics.
The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...
Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...
When building AI, you change many things at once: code, data, prompts, models. After a few runs, it becomes unclear what actually caused results to improve or regress. LitLogger records every run as ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New machine-learning tools could help organizations flag more phishing sites before ...
This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results