Search Results for author:
Found 4 papers, 2 papers with code
CERN for AGI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment
This paper explores the potential of a multidisciplinary approach to testing and aligning artificial general intelligence (AGI) and LLMs.
Identifying Individual Dogs in Social Media Images
We present the results of an initial study focused on developing a visual AI solution able to recognize individual dogs in unconstrained (wild) images occurring on social media.
Self Paced Deep Learning for Weakly Supervised Object Detection
The main idea is to iteratively select a subset of images and boxes that are the most reliable, and use them for training.
Ranked #31 on
Weakly Supervised Object Detection
on PASCAL VOC 2007
Unsupervised Tube Extraction Using Transductive Learning and Dense Trajectories
The combination of appearance-based static ''objectness'' (Selective Search), motion information (Dense Trajectories) and transductive learning (detectors are forced to "overfit" on the unsupervised data used for training) makes the proposed approach extremely robust.
