Papers Scene Classification
“Scene Classification” 태그가 달린 논문 497편 · 필터 해제
Impact of Acoustic Event Tagging on Scene Classification in a Multi-Task Learning Framework
Acoustic events are sounds with well-defined spectro-temporal characteristics which can be associated with the physical objects generating them. Acoustic scenes are collections of such acoustic events in no specific temp…
Acoustic Scene ClassificationMulti-Task LearningScene ClassificationBYOL-S: Learning Self-supervised Speech Representations by Bootstrapping
Methods for extracting audio and speech features have been studied since pioneering work on spectrum analysis decades ago. Recent efforts are guided by the ambition to develop general-purpose audio representations. For e…
Scene ClassificationSelf-Supervised LearningDomain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification
While using two-dimensional convolutional neural networks (2D-CNNs) in image processing, it is possible to manipulate domain information using channel statistics, and instance normalization has been a promising way to ge…
Acoustic Scene ClassificationDomain GeneralizationScene ClassificationRemote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network
The task of remote sensing image scene classification (RSISC), which aims at classifying remote sensing images into groups of semantic categories based on their contents, has taken the important role in a wide range of a…
Deep Learningimage-classificationImage Classificationobject-detection+4DCASE 2022: Comparative Analysis Of CNNs For Acoustic Scene Classification Under Low-Complexity Considerations
Acoustic scene classification is an automatic listening problem that aims to assign an audio recording to a pre-defined scene based on its audio data. Over the years (and in past editions of the DCASE) this problem has o…
Acoustic Scene ClassificationScene ClassificationLow-complexity deep learning frameworks for acoustic scene classification
In this report, we presents low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed frameworks can be separated into four main steps: Front-end spectrogram extraction, online data au…
Acoustic Scene ClassificationClassificationData AugmentationDeep Learning+1Low-complexity acoustic scene classification in DCASE 2022 Challenge
This paper presents an analysis of the Low-Complexity Acoustic Scene Classification task in DCASE 2022 Challenge. The task was a continuation from the previous years, but the low-complexity requirements were changed to t…
Acoustic Scene ClassificationClassificationQuantizationScene ClassificationSelf-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment
Learning from audio-visual data offers many possibilities to express correspondence between the audio and visual content, similar to the human perception that relates aural and visual information. In this work, we presen…
Acoustic Scene ClassificationAction Recognitionobject-detectionObject Detection+4Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification
Remote sensing scene classification aims to assign automatically each aerial image a specific sematic label. In this letter, we propose a new method, called self-attention-based deep feature fusion (SAFF), to aggregate d…
ClassificationRemote Sensing Image ClassificationScene ClassificationWaveMix: A Resource-efficient Neural Network for Image Analysis
We propose a novel neural architecture for computer vision -- WaveMix -- that is resource-efficient and yet generalizable and scalable. While using fewer trainable parameters, GPU RAM, and computations, WaveMix networks …
Efficient Neural NetworkGPUImage ClassificationScene Classification+2Learning Instance Representation Banks for Aerial Scene Classification
Aerial scenes are more complicated in terms of object distribution and spatial arrangement than natural scenes due to the bird view, and thus remain challenging to learn discriminative scene representation. Recent soluti…
Aerial Scene ClassificationClassificationMultiple Instance LearningScene ClassificationPairwise Comparison Network for Remote Sensing Scene Classification
Remote sensing scene classification aims to assign a specific semantic label to a remote sensing image. Recently, convolutional neural networks have greatly improved the performance of remote sensing scene classification…
ClassificationScene ClassificationAll Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
Aerial scene classification remains challenging as: 1) the size of key objects in determining the scene scheme varies greatly; 2) many objects irrelevant to the scene scheme are often flooded in the image. Hence, how to …
Aerial Scene ClassificationAllImage ClassificationMultiple Instance Learning+2A Comparative Study on Approaches to Acoustic Scene Classification using CNNs
Acoustic scene classification is a process of characterizing and classifying the environments from sound recordings. The first step is to generate features (representations) from the recorded sound and then classify the …
Acoustic Scene ClassificationClassificationScene ClassificationAudio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy
Recently, audio-visual scene classification (AVSC) has attracted increasing attention from multidisciplinary communities. Previous studies tended to adopt a pipeline training strategy, which uses well-trained visual and …
Scene ClassificationTransfer LearningA high-resolution canopy height model of the Earth
The worldwide variation in vegetation height is fundamental to the global carbon cycle and central to the functioning of ecosystems and their biodiversity. Geospatially explicit and, ideally, highly resolved information …
Decision MakingProbabilistic Deep LearningScene ClassificationVocal Bursts Intensity PredictionTOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning
Do we on the right way for remote sensing image understanding (RSIU) by training models via supervised data-dependent and task-dependent way, instead of human vision in a label-free and task-independent way? We argue tha…
General Knowledgeobject-detectionObject DetectionScene Classification+21-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality
This paper presents an alternate representation framework to commonly used time-frequency representation for acoustic scene classification (ASC). A raw audio signal is represented using a pre-trained convolutional neural…
Acoustic Scene ClassificationDictionary LearningDimensionality ReductionScene ClassificationA Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification
We present a method to develop low-complexity convolutional neural networks (CNNs) for acoustic scene classification (ASC). The large size and high computational complexity of typical CNNs is a bottleneck for their deplo…
Acoustic Scene ClassificationScene ClassificationA Multi-Stage Duplex Fusion ConvNet for Aerial Scene Classification
Existing deep learning based methods effectively prompt the performance of aerial scene classification. However, due to the large amount of parameters and computational cost, it is rather difficult to apply these methods…
Aerial Scene ClassificationScene Classification