Search Results for "framework-arduinoststm32"

fairseq-lua is the original Lua/Torch7 version of Facebook AI Research’s sequence modeling toolkit, designed for neural machine translation (NMT) and sequence generation. It introduced early attention-based architectures and training pipelines that later evolved into the modern PyTorch-based fairseq. The framework implements sequence-to-sequence models with attention, beam search decoding, and distributed training, providing a research platform for exploring translation, summarization...

MultiPathNet is a Torch-7 implementation of the “A MultiPath Network for Object Detection” paper (BMVC 2016), developed by Facebook AI Research. It extends the Fast R-CNN framework by introducing multiple network “paths” to enhance feature extraction and object recognition robustness. The MultiPath architecture incorporates skip connections and multi-scale processing to capture both fine-grained details and high-level context within a single detection pipeline. This results in improved...

BoomBot is a developer's framework for writing a bot connecting to the AIM network. It manages the network communication for the bots so that they can be easily written without worrying about AIM itself at all. Bots can be written in Objective-C or Lua.

CoPP is an object-oriented framework for developing algorithms for robot path planning. One of of the design goals is to make it easy to make comparisons between various path planning algorithms.