Papers Scene Classification
“Scene Classification” 태그가 달린 논문 497편 · 필터 해제
Pretraining Billion-scale Geospatial Foundational Models on Frontier
As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models…
Scene ClassificationSelf-Supervised LearningExploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification
Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Despite the significant performance boost in…
object-detectionObject DetectionScene ClassificationSegmentation+1Bridging Remote Sensors with Multisensor Geospatial Foundation Models
In the realm of geospatial analysis, the diversity of remote sensors, encompassing both optical and microwave technologies, offers a wealth of distinct observational capabilities. Recognizing this, we present msGFM, a mu…
Cloud RemovalDiversityScene ClassificationVHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis
This paper develops a Versatile and Honest vision language Model (VHM) for remote sensing image analysis. VHM is built on a large-scale remote sensing image-text dataset with rich-content captions (VersaD), and an honest…
HallucinationImage CaptioningLanguage ModelingLanguage Modelling+6RSMamba: Remote Sensing Image Classification with State Space Model
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements of Convolutional Neural Networks (CNNs) …
Classificationimage-classificationImage ClassificationMamba+2Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling
As repositories of large scale data in earth observation (EO) have grown, so have transfer and storage costs for model training and inference, expending significant resources. We introduce Neural Embedding Compression (N…
Earth ObservationScene ClassificationSemantic SegmentationLeveraging feature communication in federated learning for remote sensing image classification
In the realm of Federated Learning (FL) applied to remote sensing image classification, this study introduces and assesses several innovative communication strategies. Our exploration includes feature-centric communicati…
ClassificationFederated Learningimage-classificationImage Classification+2MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods …
Aerial Scene ClassificationBuilding change detection for remote sensing imagesChange DetectionChange detection for remote sensing images+13Leveraging Self-Supervised Learning for Scene Classification in Child Sexual Abuse Imagery
Crime in the 21st century is split into a virtual and real world. However, the former has become a global menace to people's well-being and security in the latter. The challenges it presents must be faced with unified gl…
Scene ClassificationScene RecognitionSelf-Supervised LearningComparing Importance Sampling Based Methods for Mitigating the Effect of Class Imbalance
Most state-of-the-art computer vision models heavily depend on data. However, many datasets exhibit extreme class imbalance which has been shown to negatively impact model performance. Among the training-time and data-ge…
Scene ClassificationEfficient Multi-Resolution Fusion for Remote Sensing Data with Label Uncertainty
Multi-modal sensor data fusion takes advantage of complementary or reinforcing information from each sensor and can boost overall performance in applications such as scene classification and target detection. This paper …
Scene ClassificationDescription on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift
Acoustic scene classification (ASC) is a crucial research problem in computational auditory scene analysis, and it aims to recognize the unique acoustic characteristics of an environment. One of the challenges of the ASC…
Acoustic Scene ClassificationScene ClassificationDeep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene Classification
Deep neural networks have achieved promising progress in remote sensing (RS) image classification, for which the training process requires abundant samples for each class. However, it is time-consuming and unrealistic to…
Attributeimage-classificationImage ClassificationScene Classification+3Knowledge-Aware Neuron Interpretation for Scene Classification
Although neural models have achieved remarkable performance, they still encounter doubts due to the intransparency. To this end, model prediction explanation is attracting more and more attentions. However, current metho…
ClassificationScene ClassificationBayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori
In this work, we aim to establish a Bayesian adaptive learning framework by focusing on estimating latent variables in deep neural network (DNN) models. Latent variables indeed encode both transferable distributional inf…
Acoustic Scene ClassificationScene ClassificationTransfer LearningDigital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems
Computer-based scene understanding has influenced fields ranging from urban planning to autonomous vehicle performance, yet little is known about how well these technologies work across social differences. We investigate…
Scene ClassificationScene RecognitionScene UnderstandingA Volumetric Saliency Guided Image Summarization for RGB-D Indoor Scene Classification
Image summary, an abridged version of the original visual content, can be used to represent the scene. Thus, tasks such as scene classification, identification, indexing, etc., can be performed efficiently using the uniq…
Saliency DetectionScene ClassificationGeneric Knowledge Boosted Pre-training For Remote Sensing Images
Deep learning models are essential for scene classification, change detection, land cover segmentation, and other remote sensing image understanding tasks. Most backbones of existing remote sensing deep learning models a…
Change DetectionDeep LearningGeneral Knowledgeobject-detection+3Kronecker Product Feature Fusion for Convolutional Neural Network in Remote Sensing Scene Classification
Remote Sensing Scene Classification is a challenging and valuable research topic, in which Convolutional Neural Network (CNN) has played a crucial role. CNN can extract hierarchical convolutional features from remote sen…
Scene ClassificationSkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing
Remote sensing imagery, despite its broad applications in helping achieve Sustainable Development Goals and tackle climate change, has not yet benefited from the recent advancements of versatile, task-agnostic vision lan…
AttributeCross-Modal RetrievalImage GenerationRetrieval+1