7 papers
Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI
Sai Teja Erukude, Lior Shamir
While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that of space-based telescopes. Sp…
GRAZE: Grounded Refinement and Motion-Aware Zero-Shot Event Localization
Syed Ahsan Masud Zaidi, Lior Shamir, William Hsu +2
American football practice generates video at scale, yet the interaction of interest occupies only a brief window of each long, untrimmed clip. Reliable biomechanical analysis, the…
Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images
Michael Okonoda, Eder Martinez, Abhilekha Dalal +1
Convolutional Neural Networks have shown promising effectiveness in identifying different types of cancer from radiographs. However, the opaque nature of CNNs makes it difficult to…
CornViT: A Multi-Stage Convolutional Vision Transformer Framework for Hierarchical Corn Kernel Analysis
Sai Teja Erukude, Jane Mascarenhas, Lior Shamir
Accurate grading of corn kernels is critical for seed certification, directional seeding, and breeding, yet it is still predominantly performed by manual inspection. This work intr…
An open dataset of neural networks for hypernetwork research
David Kurtenbach, Lior Shamir
Despite the transformative potential of AI, the concept of neural networks that can produce other neural networks by generating model weights (hypernetworks) has been largely under…
Galaxy image simplification using Generative AI
Sai Teja Erukude, Lior Shamir
Modern digital sky surveys have been acquiring images of billions of galaxies. While these images often provide sufficient details to analyze the shape of the galaxies, accurate an…