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by Google Research · 0 reviews

Deep convolutional neural network trained on ImageNet for classifying images into object categories with high accuracy.

by Meta AI · 0 reviews

Foundation model for promptable visual segmentation in images and videos, enabling real-time object tracking and zero-shot generalization to unseen content.

by scikit-learn · 0 reviews

An efficient unsupervised anomaly detection algorithm that isolates anomalies through random partitioning, robust to high-dimensional data.

by Microsoft Research · 0 reviews

Deep residual learning network architecture that enables training of very deep neural networks through skip connections for image classification tasks.

by Google Research · 0 reviews

Family of convolutional neural networks that use compound scaling to uniformly scale depth, width, and resolution for efficient image classification.

by Google Research · 0 reviews

Lightweight family of convolutional neural networks designed for efficient inference on mobile and embedded devices with minimal computational overhead.

by Google Research · 0 reviews

Applies transformers directly to image patches for classification; inspired many CV variants.

by Ultralytics · 0 reviews

The latest YOLO family model for real-time object detection, classification, and segmentation.

by Meta AI · 0 reviews

A promptable zero-shot image segmentation model trained on 1.1B masks over 11M images.