--- id: "/non-llm-neural-networks-ml-foundations/vision/page/2/" title: "vision: 44 curated resources · page 2" url: "https://skillissue.dev/non-llm-neural-networks-ml-foundations/vision/page/2/" --- # vision: 44 curated resources vision [Beginner](/non-llm-neural-networks-ml-foundations/beginner/index.md) [Intermediate](/non-llm-neural-networks-ml-foundations/intermediate/index.md) [Advanced](/non-llm-neural-networks-ml-foundations/advanced/index.md) [Expert](/non-llm-neural-networks-ml-foundations/expert/index.md) 44 resources · page 2 of 2 - ### [Faster R-CNN](/foundations/llm-fundamentals/faster-r-cnn/index.md) by [Shaoqing Ren et al. (Microsoft Research)](https://www.microsoft.com/en-us/research/) NeurIPS paper (PDF, 2015) Faster R-CNN: real-time object detection with region proposal networks. Advanced–Expert learning_resource paper CN zh - ### [Inception / GoogLeNet](/foundations/llm-fundamentals/inception-googlenet/index.md) by [Christian Szegedy et al. (Google)](https://ai.google/) arXiv PDF of the GoogLeNet paper (2014) introducing the Inception architecture. Advanced–Expert learning_resource paper US - ### [Mask R-CNN](/foundations/llm-fundamentals/mask-r-cnn/index.md) by [Kaiming He et al. (Facebook AI Research)](https://ai.meta.com/) arXiv paper (2017) "Mask R-CNN", introducing Mask R-CNN for instance segmentation. Advanced–Expert learning_resource paper West en - ### [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](/foundations/llm-fundamentals/mobilenet/index.md) by [Andrew G. Howard et al. (Google)](https://ai.google/) arXiv PDF of the MobileNets paper (2017) on efficient convolutional networks for mobile vision. Advanced–Expert learning_resource paper US - ### [Moirai](/foundations/llm-fundamentals/moirai/index.md) by [Gerald Woo et al. (Salesforce)](https://www.salesforce.com/) arXiv PDF of the Moirai paper (2024), Salesforce's universal time-series forecasting transformer. Advanced–Expert learning_resource paper Global (Salesforce AI Research - ### [ResNet](/foundations/llm-fundamentals/resnet/index.md) by [Kaiming He et al. (Microsoft)](https://www.microsoft.com/) arXiv paper (2015) "Deep Residual Learning for Image Recognition", introducing ResNet residual networks. Advanced–Expert learning_resource paper West en - ### [SAM](/foundations/llm-fundamentals/sam/index.md) by [Alexander Kirillov et al. (Meta AI)](https://ai.meta.com/) arXiv paper (2023) introducing Segment Anything (SAM), a promptable image segmentation model and dataset. Advanced–Expert learning_resource paper US en - ### [A decoder-only foundation model for time-series forecasting (TimesFM)](/foundations/llm-fundamentals/timesfm-2/index.md) by [Abhimanyu Das et al. (Google)](https://ai.google/) arXiv paper (2023) introducing TimesFM, a decoder-only foundation model for time-series forecasting. Advanced–Expert learning_resource paper US en - ### [U-Net](/foundations/llm-fundamentals/u-net/index.md) by [Olaf Ronneberger et al. (University of Freiburg)](https://www.uni-freiburg.de) arXiv paper (2015) "U-Net: Convolutional Networks for Biomedical Image Segmentation", introducing the encoder-decoder architecture with skip connections. Advanced–Expert learning_resource paper West en - ### [VGG](/foundations/llm-fundamentals/vgg/index.md) by [Karen Simonyan and Andrew Zisserman (University of Oxford)](https://www.ox.ac.uk/) arXiv PDF of the VGG paper (2014) on very deep convolutional networks for large-scale image recognition. Advanced–Expert learning_resource paper Europe — UK - ### [ViT](/foundations/llm-fundamentals/vit/index.md) by [Alexey Dosovitskiy et al. (Google)](https://ai.google/) arXiv paper (2020) introducing the Vision Transformer (ViT) for image recognition. Advanced–Expert learning_resource paper West en - ### [YOLO](/foundations/llm-fundamentals/yolo/index.md) by [Joseph Redmon et al. (University of Washington)](https://www.washington.edu/) arXiv paper (2015) "You Only Look Once: Unified, Real-Time Object Detection", introducing YOLO, a single-stage real-time object detector. Advanced learning_resource paper West en [Previous page](/non-llm-neural-networks-ml-foundations/vision/index.md) [Plain-text Markdown copy](/non-llm-neural-networks-ml-foundations/vision/page/2/index.md)