remove dead

README.md

@@ -946,7 +946,7 @@ Extracting roads is challenging due to the occlusions caused by other objects an
 
 - [EG-UNet](https://github.com/tist0bsc/EG-UNet) Deep Feature Enhancement Method for Land Cover With Irregular and Sparse Spatial Distribution Features: A Case Study on Open-Pit Mining
 
-- [plastics](https://github.com/earthrise-media/plastics) -> Detecting and Monitoring Plastic Waste Aggregations in Sentinel-2 Imagery for [globalplasticwatch.org](https://globalplasticwatch.org/)
+- [plastics](https://github.com/earthrise-media/plastics) -> Detecting and Monitoring Plastic Waste Aggregations in Sentinel-2 Imagery
 
 - [MADOS](https://github.com/gkakogeorgiou/mados) -> Detecting Marine Pollutants and Sea Surface Features with Deep Learning in Sentinel-2 Imagery on the MADOS dataset
 
@@ -1599,8 +1599,6 @@ A variety of techniques can be used to count animals, including object detection
 
 - [Electric-Pylon-Detection-in-RSI](https://github.com/qsjxyz/Electric-Pylon-Detection-in-RSI) -> a dataset which contains 1500 remote sensing images of electric pylons used to train ten deep learning models
 
-- [Synthesizing Robustness YOLTv4 Results Part 2: Dataset Size Requirements and Geographic Insights](https://www.iqt.org/synthesizing-robustness-yoltv4-results-part-2-dataset-size-requirements-and-geographic-insights/) -> quantify how much harder rare objects are to localize
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 - [IS-Count](https://github.com/sustainlab-group/IS-Count) -> IS-Count is a sampling-based and learnable method for estimating the total object count in a region
 
 - [Object Detection On Aerial Imagery Using RetinaNet](https://towardsdatascience.com/object-detection-on-aerial-imagery-using-retinanet-626130ba2203)
@@ -3700,10 +3698,6 @@ Training data can be hard to acquire, particularly for rare events such as chang
 
 - [oktal-se](https://www.oktal-se.fr/deep-learning/) -> software for generating simulated data across a wide range of bands including optical and SAR
 
-- [The Nuances of Extracting Utility from Synthetic Data](https://www.iqt.org/synthesizing-robustness-yoltv4-results-part-1/) -> We find that strategically augmenting the real dataset is nearly as effective as adding synthetic data in the quest to improve the detection or rare object classes, and that fully extracting the utility of synthetic data is a nuanced process
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-- [Synthesizing Robustness](https://www.iqt.org/synthesizing-robustness/) -> explores how to best leverage and enhance synthetic data
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 - [rendered.ai](https://rendered.ai/) -> The Platform as a Service for Creating Synthetic Data
 
 - [synthetic_xview_airplanes](https://github.com/yangxu351/synthetic_xview_airplanes) -> creation of airplanes synthetic dataset using ArcGIS CityEngine