Papers Scene Classification
“Scene Classification” 태그가 달린 논문 497편 · 필터 해제
APLA: A Simple Adaptation Method for Vision Transformers
Existing adaptation techniques typically require architectural modifications or added parameters, leading to high computational costs and complexity. We introduce Attention Projection Layer Adaptation (APLA), a simple ap…
ClassificationGPUScene ClassificationRoMA: Scaling up Mamba-based Foundation Models for Remote Sensing
Recent advances in self-supervised learning for Vision Transformers (ViTs) have fueled breakthroughs in remote sensing (RS) foundation models. However, the quadratic complexity of self-attention poses a significant barri…
Computational EfficiencyMambaobject-detectionObject Detection+3Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification
Due to the difficulty of obtaining labeled data for hyperspectral images (HSIs), cross-scene classification has emerged as a widely adopted approach in the remote sensing community. It involves training a model using lab…
ClassificationHyperspectral Image Classificationimage-classificationImage Classification+1Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer
In this work, we propose a novel variational Bayesian adaptive learning approach for cross-domain knowledge transfer to address acoustic mismatches between training and testing conditions, such as recording devices and e…
Acoustic Scene ClassificationScene ClassificationSpoken Command RecognitionTransfer Learning+1A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features
Scene understanding in remote sensing often faces challenges in generating accurate representations for complex environments such as various land use areas or coastal regions, which may also include snow, clouds, or haze…
Language ModelingLanguage ModellingScene ClassificationScene UnderstandingLWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
Remote sensing (RS) visual tasks have gained significant academic and practical importance. However, they encounter numerous challenges that hinder effective feature extraction, including the detection and recognition of…
Change DetectionImage Classificationobject-detectionObject Detection+4Quantum-Enhanced Transformers for Robust Acoustic Scene Classification in IoT Environments
The proliferation of Internet of Things (IoT) devices equipped with acoustic sensors necessitates robust acoustic scene classification (ASC) capabilities, even in noisy and data-limited environments. Traditional machine …
Acoustic Scene ClassificationData AugmentationScene ClassificationMulti-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution
Satellite imagery is a cornerstone for numerous Remote Sensing (RS) applications; however, limited spatial resolution frequently hinders the precision of such systems, especially in multi-label scene classification tasks…
ClassificationImage Super-ResolutionScene ClassificationSuper-ResolutionVision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding
Scene understanding is essential for enhancing driver safety, generating human-centric explanations for Automated Vehicle (AV) decisions, and leveraging Artificial Intelligence (AI) for retrospective driving video analys…
Autonomous DrivingIn-Context LearningScene ClassificationScene Recognition+1Enhancing Scene Classification in Cloudy Image Scenarios: A Collaborative Transfer Method with Information Regulation Mechanism using Optical Cloud-Covered and SAR Remote Sensing Images
In remote sensing scene classification, leveraging the transfer methods with well-trained optical models is an efficient way to overcome label scarcity. However, cloud contamination leads to optical information loss and …
Cloud RemovalKnowledge DistillationScene ClassificationTransfer LearningFedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models
Remote sensing data is often distributed across multiple institutions, and due to privacy concerns and data-sharing restrictions, leveraging large-scale datasets in a centralized training framework is challenging. Federa…
Federated Learningimage-classificationImage ClassificationPrompt Learning+3UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language Models
The domain gap between remote sensing imagery and natural images has recently received widespread attention and Vision-Language Models (VLMs) have demonstrated excellent generalization performance in remote sensing multi…
Question AnsweringScene ClassificationVisual Question AnsweringImproving Acoustic Scene Classification in Low-Resource Conditions
Acoustic Scene Classification (ASC) identifies an environment based on an audio signal. This paper explores ASC in low-resource conditions and proposes a novel model, DS-FlexiNet, which combines depthwise separable convo…
Acoustic Scene ClassificationClassificationData AugmentationKnowledge Distillation+3How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning
Uncertainty quantification (UQ) is essential for assessing the reliability of Earth observation (EO) products. However, the extensive use of machine learning models in EO introduces an additional layer of complexity, as …
BenchmarkingEarth ObservationImage SegmentationScene Classification+2Multimodal Remote Sensing Scene Classification Using VLMs and Dual-Cross Attention Networks
Remote sensing scene classification (RSSC) is a critical task with diverse applications in land use and resource management. While unimodal image-based approaches show promise, they often struggle with limitations such a…
ClassificationScene Classificationtext annotationzero-shot-classification+1Neurobench: DCASE 2020 Acoustic Scene Classification benchmark on XyloAudio 2
XyloAudio is a line of ultra-low-power audio inference chips, designed for in- and near-microphone analysis of audio in real-time energy-constrained scenarios. Xylo is designed around a highly efficient integer-logic pro…
Acoustic Scene ClassificationScene ClassificationAerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia
Countries in South Asia experience many catastrophic flooding events regularly. Through image classification, it is possible to expedite search and rescue initiatives by classifying flood zones, including houses and huma…
image-classificationImage ClassificationScene ClassificationTEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data
Large vision and language assistants have enabled new capabilities for interpreting natural images. These approaches have recently been adapted to earth observation data, but they are only able to handle single image inp…
Change DetectionEarth ObservationInstruction FollowingQuestion Answering+3Less yet robust: crucial region selection for scene recognition
Scene recognition, particularly for aerial and underwater images, often suffers from various types of degradation, such as blurring or overexposure. Previous works that focus on convolutional neural networks have been sh…
Scene ClassificationScene RecognitionData Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction
In this technical report, we describe the SNTL-NTU team's submission for Task 1 Data-Efficient Low-Complexity Acoustic Scene Classification of the detection and classification of acoustic scenes and events (DCASE) 2024 c…
Acoustic Scene ClassificationData AugmentationDiversityKnowledge Distillation+1