GitHub

index.md

RMSProp is an adaptive learning rate optimization algorithm designed to handle the varying gradients across training data. This pattern helps in efficiently training deep learning models by adjusting ...
Scientific Research Publishing

Cheng, G. and Guo, W. (2017) Rock Images Classification by Using Deep Convolution Neural Network. Journal of Physics: Conference Series, 887, Article 012089.

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...
Scientific Research Publishing

Xu, Z., Ma, W., Lin, P., Shi, H., Pan, D. and Liu, T. (2021) Deep Learning of Rock Images for Intelligent Lithology Identification. Computers & Geosciences, 154, Article 104799.

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...
pv magazine International

Deep-learning tech for dust detection in solar panels

An international group of scientists developed a novel dust detection method for PV systems. The new technique is based on deep learning and utilizes an improved version of the adaptive moment ...
Search Engine Land

Google algorithm updates 2023 in review: Core, reviews, helpful content, spam and beyond

Google launched nine confirmed algorithmic updates in 2023, as well as a new AI search engine, the Search Generative Experience. In 2022 and 2021, Google had 10 confirmed algorithmic updates. Unless ...
GitHub

The goal of this repository is the implementation in Pytorch of the main optimizers existing (Adam, SGD, Adagrad, Adadelta, RMSProp) algorithms

The project is over and all main algorithms have were built. Throughout the project, if you see any improvements that could be made in the code, do not hesitate to reach out at ...