Papers Scene Classification
“Scene Classification” 태그가 달린 논문 497편 · 필터 해제
Zero-Shot Deep Domain Adaptation
Domain adaptation is an important tool to transfer knowledge about a task (e.g. classification) learned in a source domain to a second, or target domain. Current approaches assume that task-relevant target-domain data is…
ClassificationDomain AdaptationGeneral ClassificationScene Classification+1A Hybrid Approach with Multi-channel I-Vectors and Convolutional Neural Networks for Acoustic Scene Classification
In Acoustic Scene Classification (ASC) two major approaches have been followed . While one utilizes engineered features such as mel-frequency-cepstral-coefficients (MFCCs), the other uses learned features that are the ou…
Acoustic Scene ClassificationGeneral ClassificationScene ClassificationBinary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification
Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aeria…
Aerial Scene ClassificationGeneral ClassificationMaterial RecognitionScene ClassificationObject-Level Context Modeling For Scene Classification with Context-CNN
Convolutional Neural Networks (CNNs) have been used extensively for computer vision tasks and produce rich feature representation for objects or parts of an image. But reasoning about scenes requires integration between …
ClassificationGeneral ClassificationObjectScene ClassificationCross-label Suppression: A Discriminative and Fast Dictionary Learning with Group Regularization
This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we pr…
ClassificationComputational EfficiencyDictionary LearningFace Recognition+5DeepCorrect: Correcting DNN models against Image Distortions
In recent years, the widespread use of deep neural networks (DNNs) has facilitated great improvements in performance for computer vision tasks like image classification and object recognition. In most realistic computer …
ClassificationGeneral Classificationimage-classificationImage Classification+2Land Cover Classification via Multi-temporal Spatial Data by Recurrent Neural Networks
Nowadays, modern earth observation programs produce huge volumes of satellite images time series (SITS) that can be useful to monitor geographical areas through time. How to efficiently analyze such kind of information i…
ClassificationEarth ObservationGeneral ClassificationLand Cover Classification+4The 2017 DAVIS Challenge on Video Object Segmentation
We present the 2017 DAVIS Challenge on Video Object Segmentation, a public dataset, benchmark, and competition specifically designed for the task of video object segmentation. Following the footsteps of other successful …
ObjectScene ClassificationSegmentationSemantic Segmentation+3Audio Scene Classification with Deep Recurrent Neural Networks
We introduce in this work an efficient approach for audio scene classification using deep recurrent neural networks. An audio scene is firstly transformed into a sequence of high-level label tree embedding feature vector…
ClassificationGeneral ClassificationScene ClassificationRemote Sensing Image Scene Classification: Benchmark and State of the Art
Remote sensing image scene classification plays an important role in a wide range of applications and hence has been receiving remarkable attention. During the past years, significant efforts have been made to develop va…
ClassificationDiversityGeneral ClassificationScene ClassificationSemi-supervised multi-label feature selection via label correlation analysis with l1-norm graph embedding
In this paper, we propose a novel semi-supervised multi-label feature selection algorithm and apply it to three different applications: natural scene classification, web page annotation, and yeast gene functional classif…
feature selectionGraph EmbeddingMulti-Label LearningScene ClassificationUnsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition
The recent rapid and tremendous success of deep convolutional neural networks (CNN) on many challenging computer vision tasks largely derives from the accessibility of the well-annotated ImageNet and PASCAL VOC datasets.…
ClusteringGeneral ClassificationImage CategorizationScene Classification+1Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 2 Validation
The European Space Agency (ESA) defines an Earth Observation (EO) Level 2 product as a multispectral (MS) image corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its scene classificati…
Earth ObservationGeneral ClassificationLand Cover ClassificationScene Classification+2Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 1 Theory
The European Space Agency (ESA) defines an Earth Observation (EO) Level 2 product as a multispectral (MS) image corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its scene classificati…
Earth ObservationGeneral ClassificationLand Cover ClassificationScene Classification+1Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs
This work explores CNNs for the recognition of novel categories from few examples. Inspired by the transferability properties of CNNs, we introduce an additional unsupervised meta-training stage that exposes multiple top…
Action RecognitionGeneral ClassificationScene ClassificationTemporal Action LocalizationLarge Margin Discriminant Dimensionality Reduction in Prediction Space
In this paper we establish a duality between boosting and SVM, and use this to derive a novel discriminant dimensionality reduction algorithm. In particular, using the multiclass formulation of boosting and SVM we note t…
Dimensionality ReductionGeneral ClassificationPredictionScene ClassificationObject based Scene Representations using Fisher Scores of Local Subspace Projections
Several works have shown that deep CNN classifiers can be easily transferred across datasets, e.g. the transfer of a CNN trained to recognize objects on ImageNET to an object detector on Pascal VOC. Less clear, however, …
Scene ClassificationResFeats: Residual Network Based Features for Image Classification
Deep residual networks have recently emerged as the state-of-the-art architecture in image segmentation and object detection. In this paper, we propose new image features (called ResFeats) extracted from the last convolu…
ClassificationDimensionality ReductionGeneral Classificationimage-classification+7Adaptive Deep Pyramid Matching for Remote Sensing Scene Classification
Convolutional neural networks (CNNs) have attracted increasing attention in the remote sensing community. Most CNNs only take the last fully-connected layers as features for the classification of remotely sensed images, …
ClassificationGeneral Classificationimage-classificationImage Classification+2Regularized Optimal Transport and the Rot Mover's Distance
This paper presents a unified framework for smooth convex regularization of discrete optimal transport problems. In this context, the regularized optimal transport turns out to be equivalent to a matrix nearness problem …
Scene Classification