An accurate and efficient deep learning method for single-cell RNA-seq data imputation
Food Classification with Deep Learning in Keras / Tensorflow
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
A tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) model.
Considering an open-source Mask R-CNN implementation, which is a deep multitask learning solution for object detection, instance segmentation and keypoint annotations. The current task involves given an annotated instance segmentation image and the original image, the pixel level accuracy of each instance/class from the image is calculated. This implementation does not contain any fine-tuning to support extra classes than what the model has been trained for initially.
Improving the forecasting accuracy of ENSO through deep learning
Reading irctc captchas with 98% accuracy using deep learning