IEEE

Synergistic Prompting Learning for Human-Object Interaction Detection

Abstract: Human-Object Interaction (HOI) detection, as a foundational task in human-centric understanding, aims to detect interactive triplets in real-world scenarios. To better distinguish diverse ...
earth

Some dogs can learn the names of hundreds of objects

Curiosity shapes many moments in our daily lives. It can also shape the minds of other species. A new study suggests that curiosity may be one of the hidden forces behind an unusual talent seen in a ...
IEEE

Flow-Based Metadata with Robust Machine Learning Approaches for Application Classification in Diverse Network Traffic

G and beyond 5G networks continuously evolve with new technologies, protocols, and standards to support high-speed data transfer. Traffic monitoring and analysis in these environments help perform ...
GitHub

MR-CLIP: Efficient Metadata-Guided Learning of MRI Contrast Representations

Challenge: The interpretation and analysis of Magnetic Resonance Imaging scans in clinical AI systems rely on accurate understanding of image contrast. While contrast is determined by acquisition ...
GitHub

CM3P: Contrastive Metadata-Map Masked Pre-training

CM3P (Contrastive Metadata-Map Masked Pre-training) is a multi-modal representation learning framework for osu! beatmaps. It learns high-quality embeddings for both beatmap structure (events, timing, ...