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Scene Classification

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Scene Classification is a task in which scenes from photographs are categorically classified. Unlike object classification, which focuses on classifying prominent objects in the foreground, Scene Classification uses the layout of objects within the scene, in addition to the ambient context, for classification.

Source: Scene classification with Convolutional Neural Networks

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/201528014227051/RSICD_optimal

공식 코드

Exploring Models and Data for Remote Sensing Image Caption Generation

https://github.com/Arshdeep-Singh-Boparai/passive-filter-pruning-Interspeech22

공식 코드

A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification

https://github.com/ArturoDeza/EmergentProperties

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Emergent Properties of Foveated Perceptual Systems

https://github.com/AyushiSinha/AutoInitialization

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Towards automatic initialization of registration algorithms using simulated endoscopy images

https://github.com/BUPTLdy/RICE_DATASET

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A Remote Sensing Image Dataset for Cloud Removal

https://github.com/CPJKU/dcase2024_task1_baseline

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Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge

https://github.com/GeoX-Lab/G-RSIM

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TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning

https://github.com/IntelliSensing/UniRS

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UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language Models

https://github.com/Jungjee/DcaseNet

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DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and events

https://github.com/KochPJ/vanishing-depth

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Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image Encoders

https://github.com/KyanChen/RSMamba

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RSMamba: Remote Sensing Image Classification with State Space Model

https://github.com/MihawkHu/DCASE2020_task1

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Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation

https://github.com/NJU-LHRS/official-CMID

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CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding

https://github.com/OptimusPrimus/dcase2019_task1b

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Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification

https://github.com/SRPOL-AUI/spectrum-correction

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Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices

https://github.com/SenHe/uavdvsm

공식 코드

Understanding and Visualizing Deep Visual Saliency Models

https://github.com/ShawMask/congater_dcase2022t1

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Domain Information Control at Inference Time for Acoustic Scene Classification

https://github.com/Shubhajit412/ACOUSTIC_SCENE_CLASSIFICATION_USING_AUDITORY_DATASETS

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Acoustic scene classification using auditory datasets

https://github.com/StarsThu2016/ApproxDet

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ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles

https://github.com/ZhangLi-CS/GCP_Optimization

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Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization

https://github.com/aliayub7/CBCL_RGBD

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Centroid Based Concept Learning for RGB-D Indoor Scene Classification

https://github.com/anwarmaxsum/unisa

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Unsupervised Few-Shot Continual Learning for Remote Sensing Image Scene Classification

https://github.com/arshdeep-singh-boparai/efficient_similarity_pruning_algo

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Efficient Similarity-based Passive Filter Pruning for Compressing CNNs

https://github.com/aymanbegh/cd-coco

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CD-COCO: A Versatile Complex Distorted COCO Database for Scene-Context-Aware Computer Vision

https://github.com/aymanbegh/hybrid-gcnn-cnn

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A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection Inference

https://github.com/bhanukaManesha/embarrassingly-simple-classifier-comparison

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An embarrassingly simple comparison of machine learning algorithms for indoor scene classification

https://github.com/biqiwhu/agos

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All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification

https://github.com/boranhan/geospatial_foundation_models

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Bridging Remote Sensors with Multisensor Geospatial Foundation Models

https://github.com/chrieke/awesome-satellite-imagery-datasets

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SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion

https://github.com/ckyrkou/EmergencyNet

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Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles

https://github.com/cochlearai/cochlscene

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CochlScene: Acquisition of acoustic scene data using crowdsourcing

https://github.com/cpjku/dcase2025_task1_baseline

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Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge

https://github.com/cugbrs/MLRSNet

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MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene Understanding

https://github.com/daniilidis-group/emvn

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Equivariant Multi-View Networks

https://github.com/davidbau/dissect

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Understanding the Role of Individual Units in a Deep Neural Network

https://github.com/dr-costas/undaw

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Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene Classification

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