all AI news
UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation
May 7, 2024, 4:48 a.m. | Abdelrahman Shaker, Muhammad Maaz, Hanoona Rasheed, Salman Khan, Ming-Hsuan Yang, Fahad Shahbaz Khan
cs.CV updates on arXiv.org arxiv.org
Abstract: Owing to the success of transformer models, recent works study their applicability in 3D medical segmentation tasks. Within the transformer models, the self-attention mechanism is one of the main building blocks that strives to capture long-range dependencies. However, the self-attention operation has quadratic complexity which proves to be a computational bottleneck, especially in volumetric medical imaging, where the inputs are 3D with numerous slices. In this paper, we propose a 3D medical image segmentation approach, …
More from arxiv.org / cs.CV updates on arXiv.org
Multi-View Spectrogram Transformer for Respiratory Sound Classification
2 days, 22 hours ago |
arxiv.org
GaussianHead: High-fidelity Head Avatars with Learnable Gaussian Derivation
2 days, 22 hours ago |
arxiv.org
OTMatch: Improving Semi-Supervised Learning with Optimal Transport
2 days, 22 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Senior Applied Data Scientist
@ dunnhumby | London
Principal Data Architect - Azure & Big Data
@ MGM Resorts International | Home Office - US, NV