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Found 7 papers, 6 papers with code
A Simple Aerial Detection Baseline of Multimodal Language Models
In this paper, we present a simple baseline for applying MLMs to aerial detection for the first time, named LMMRotate.
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
In this paper, we introduce OmniCorpus, a 10 billion-scale image-text interleaved dataset.
Spectral-Spatial Mamba for Hyperspectral Image Classification
Among the many deep models, Transformer has gradually attracted interest for its excellence in modeling the long-range dependencies of spatial-spectral features in HSI.
The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World
We present the All-Seeing (AS) project: a large-scale data and model for recognizing and understanding everything in the open world.
ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object Detection
Existing oriented object detection methods commonly use metric AP$_{50}$ to measure the performance of the model.
Deep Learning for Hyperspectral Image Classification: An Overview
Specifically, we first summarize the main challenges of HSI classification which cannot be effectively overcome by traditional machine learning methods, and also introduce the advantages of deep learning to handle these problems.
Spectral-Spatial Classification of Hyperspectral Image Using Autoencoders
Hyperspectral image (HSI) classification is a hot topic in the remote sensing community.
