Update README.md

README.md

@@ -942,6 +942,7 @@ Generally speaking, change detection methods are applied to a pair of images to
 * [IRCNN](https://github.com/thebinyang/IRCNN) -> code for 2022 [paper](https://ieeexplore.ieee.org/abstract/document/9721897): IRCNN: An Irregular-Time-Distanced Recurrent Convolutional Neural Network for Change Detection in Satellite Time Series
 * [UTRNet](https://github.com/thebinyang/UTRNet) -> An Unsupervised Time-Distance-Guided Convolutional Recurrent Network for Change Detection in Irregularly Collected Images
 * [open-cd](https://github.com/likyoo/open-cd) -> an open source change detection toolbox based on a series of open source general vision task tools
+* [Tiny_model_4_CD](https://github.com/AndreaCodegoni/Tiny_model_4_CD) -> code for 2022 [paper](https://arxiv.org/abs/2207.13159): TINYCD: A (Not So) Deep Learning Model For Change Detection. Uses LEVIR-CD & WHU-CD datasets
 
 ## Time series
 More general than change detection, time series observations can be used for applications including improving the accuracy of crop classification, or predicting future patterns & events. Crop yield is very typically application and has its own section below