Tensorflow
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Image quality is an open source software library for Image Quality Assessment (IQA).
Annotated notes and summaries of the TensorFlow white paper, with SVG figures and links to documentation.
Deep learning models for crop yield prediction using remote sensing data, with CNN/LSTM and Gaussian Process approaches.
A practical demo using LSTM neural networks with TensorFlow to predict lottery numbers.
Interactive visualization tool for understanding Capsule Network (CapsNet) layers and their internal workings.
A Ruby gem providing TensorFlow bindings for basic tensor operations and machine learning tasks.
A collection of open-source machine learning and quantitative analysis models implemented in TensorFlow and PyTorch.
A neural networks toolbox for medical image analysis, providing specialized layers, models, and utilities for TensorFlow/Keras.
An easy-to-use C# deep learning library with support for multiple backends including TensorFlow, PyTorch, and CUDA/OpenCL.
A real-time RGB-based pipeline for object detection and 6D pose estimation using a denoising autoencoder trained on simulated 3D views.
TensorFlow implementation of weakly-supervised object localization using only image-level labels, without bounding box annotations.
Deploy TensorFlow graphs for fast evaluation and export to environments without TensorFlow, using NumPy.
A TensorFlow implementation of End-To-End Memory Networks with a scikit-learn-like interface for bAbI tasks.
A Python toolbox for content-aware restoration of fluorescence microscopy images using deep learning.
A Docker-based image annotation tool for bounding box labeling with auto-labeling support, designed for deep learning training.
A deep learning architecture using stacked residual bidirectional LSTM cells with TensorFlow for human activity recognition from sensor data.
Tensorflow bindings for the Elixir programming language, enabling machine learning inference and tensor operations.
Deep learning model using convolutional neural networks to predict drug-target binding affinity from protein sequences and compound SMILES.
A TensorFlow implementation of fastText for embedding-based text classification with support for character ngrams and distributed training.
A centralized Python framework for agricultural machine learning, providing access to public datasets, benchmarks, pretrained models, and synthetic data generation.
A TensorFlow-based object detection model that localizes and identifies multiple objects in images using SSD MobileNet V1 or Faster R-CNN ResNet101.
OCaml bindings for TensorFlow, enabling machine learning and neural network development in a functional programming environment.
TensorFlow and NumPy implementations of HMM Viterbi and forward/backward algorithms for sequence modeling.
A Python library for Bayesian optimization using GPflow and TensorFlow, designed for optimizing expensive black-box functions.
An open-source tool to detect and blur faces and license plates in images for privacy compliance, using TensorFlow object detection.
A deep convolutional neural network that predicts RNA-seq coverage at 32bp resolution from DNA sequence.
Trading Environment(OpenAI Gym) + PPO(TensorForce)
FLAME dataset and deep learning models for fire detection in aerial imagery using UAVs, supporting classification and segmentation tasks.
Neural machine translation between Shakespearean and modern English using TensorFlow.
A self-supervised deep learning model for extrinsic calibration between LiDAR and camera sensors using 3D spatial transformer networks.
Deep reinforcement learning framework for financial trading using price trailing, implemented with Keras-RL for Forex markets.
A large-scale driving behavior dataset with LiDAR point clouds, dashboard videos, and sensor data for autonomous driving research.
A statistical natural language generator for spoken dialogue systems, supporting both A*-search and seq2seq algorithms.
A semi-automated pipeline for instance-aware cell segmentation, tracking, and migration analysis in phase contrast microscopy using Mask R-CNN.
A TensorFlow CNN implementation for Chinese character recognition, achieving 92.5% top-1 accuracy with batch normalization.
A Scala and JVM machine learning toolbox for research, education, and industry with an interactive REPL and end-to-end pipelines.
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