Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...
Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...
Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and visualization. A ‘Trump class’ folly on the high seas Democratic voter turnout ...
Abstract: This study presents the Ear3D-PAF network, an advanced method for 3D ear point cloud reconstruction, addressing the challenges of data scarcity and complex structural geometry. The approach ...
I am a graduate student working on NeRF- and 3DGS-related things. I am facing an issuer when trying to reconstruct a scene with Splatfacto on my own dataset. The video attached below is a ...
I'm using the OMol25 dataset and I’m accessing molecular information using: atoms = dataset.get_atoms(x) I would like to reconstruct the full molecular graph, including bond connectivity and bond ...
Circadian rhythms regulate the timing of thousands of genes across human tissues, aligning physiology with the 24-hour day. However, most transcriptomic datasets lack time-of-day annotations, limiting ...
Apple’s Machine Learning team, in collaboration with researchers from Nanjing University and The Hong Kong University of Science and Technology, has announced an interesting 3D AI model called ...
ABSTRACT: Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback