Browse Articles

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Gupta et al. | Oct 18, 2020

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

Read More...

The impact of greenhouse gases, regions, and sectors on future temperature anomaly with the FaIR model

Kosaraju et al. | Jul 29, 2024

The impact of greenhouse gases, regions, and sectors on future temperature anomaly with the FaIR model

This study explores how different economic sectors, geographic regions, and greenhouse gas types might affect future global mean surface temperature (GMST) anomalies differently from historical patterns. Using the Finite Amplitude Impulse Response (FaIR) model and four Shared Socioeconomic Pathways (SSPs) — SSP126, SSP245, SSP370, and SSP585 — the research reveals that future contributions to GMST anomalies.

Read More...
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember