ConvLSTM Network

ConvLSTM networks combine convolutional neural networks (CNNs) with long short-term memory (LSTMs) to effectively process spatiotemporal data, primarily aiming to improve the accuracy of time series predictions and image segmentation. Current research focuses on enhancing ConvLSTM architectures through hybrid models incorporating transformers or other advanced techniques like ConvNeXt backbones, often applied to diverse fields such as weather forecasting, medical image analysis, and traffic prediction. These advancements demonstrate ConvLSTM's significant impact across various domains by providing more accurate and efficient solutions for complex spatiotemporal modeling tasks.