Deep Neural Networks
Showing 14 of 50 projects
A city-scale dataset and platform for learning holistic 3D structures from panoramic and perspective imagery with detailed annotations.
A lightweight, platform-independent tensor library with autograd for the JVM, accelerated by OpenCL.
A deep neural network package for Go, designed for simplicity and extensibility.
A curated archive of pre-trained computer vision models for object detection, face recognition, fire detection, and more.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A lightweight deep learning library written in C++ with C, C#, and Python interfaces, supporting CPU and GPU computation.
A Swift deep learning library for iOS and macOS with Accelerate and Metal support.
A deep learning model that translates between single-cell multi-omic profiles, such as scATAC-seq and scRNA-seq, using a shared latent representation.
An open-source solution for the Google AI Open Images Object Detection Challenge, providing a RetinaNet-based benchmark with experiment tracking.
A Ruby deep learning library supporting fully connected, convolutional, and recurrent neural networks.
A framework for automated cryptographic primitive classification using dynamic binary instrumentation and deep learning.
A Python package that integrates an LLM copilot into Keras model development to provide performance improvement suggestions.
A TensorFlow-based model that generates text summaries using pointer-generator networks, deployable as a Docker container.
An embedded deep learning library for Go designed for educational exploration of neural network fundamentals.
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