Papers Texture Classification
“Texture Classification” 태그가 달린 논문 206편 · 필터 해제
Quantitative Measures for Passive Sonar Texture Analysis
Passive sonar signals contain complex characteristics often arising from environmental noise, vessel machinery, and propagation effects. While convolutional neural networks (CNNs) perform well on passive sonar classifica…
Texture ClassificationPatch and Shuffle: A Preprocessing Technique for Texture Classification in Autonomous Cementitious Fabrication
Autonomous fabrication systems are transforming construction and manufacturing, yet they remain vulnerable to print errors. Texture classification is a key component of computer vision systems that enable real-time monit…
ClassificationTexture ClassificationVORTEX: Challenging CNNs at Texture Recognition by using Vision Transformers with Orderless and Randomized Token Encodings
Texture recognition has recently been dominated by ImageNet-pre-trained deep Convolutional Neural Networks (CNNs), with specialized modifications and feature engineering required to achieve state-of-the-art (SOTA) perfor…
Computational EfficiencyFeature EngineeringTexture ClassificationLightweight Deepfake Detection Based on Multi-Feature Fusion
Deepfake technology utilizes deep learning based face manipulation techniques to seamlessly replace faces in videos creating highly realistic but artificially generated content. Although this technology has beneficial ap…
DeepFake DetectionFace SwappingTexture ClassificationA Machine Learning Model for Crowd Density Classification in Hajj Video Frames
Managing the massive annual gatherings of Hajj and Umrah presents significant challenges, particularly as the Saudi government aims to increase the number of pilgrims. Currently, around two million pilgrims attend Hajj a…
Texture ClassificationGLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation
Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs often struggle to model local spatial information effectively, which is esse…
Cardiac SegmentationImage SegmentationMedical Image AnalysisMedical Image Segmentation+2Improving analytical color and texture similarity estimation methods for dataset-agnostic person reidentification
This paper studies a combined person reidentification (re-id) method that uses human parsing, analytical feature extraction and similarity estimation schemes. One of its prominent features is its low computational requir…
Human ParsingTexture ClassificationEmpirical curvelet based Fully Convolutional Network for supervised texture image segmentation
In this paper, we propose a new approach to perform supervised texture classification/segmentation. The proposed idea is to feed a Fully Convolutional Network with specific texture descriptors. These texture features are…
Image SegmentationSemantic SegmentationTexture ClassificationEnhanced Wavelet Scattering Network for image inpainting detection
The rapid advancement of image inpainting tools, especially those aimed at removing artifacts, has made digital image manipulation alarmingly accessible. This paper proposes several innovative ideas for detecting inpaint…
Image InpaintingImage ManipulationTexture ClassificationTexture Discrimination via Hilbert Curve Path Based Information Quantifiers
The analysis of the spatial arrangement of colors and roughness/smoothness of figures is relevant due to its wide range of applications. This paper proposes a texture classification method that extracts data from images …
Texture ClassificationAn accurate detection of micro-collapse during the lyophilisation of a 5% w/v lactose solution using a combination of novel techniques: intelligent laser speckle imaging (ILSI) and through-vial impedance spectroscopy (TVIS)
Context: In a freeze drying (FD) process, an accurate observation and control of the process parameters at critical stages are at high importance. Particularly accurate and timely identification of the critical temperatu…
Texture ClassificationA Comparative Survey of Vision Transformers for Feature Extraction in Texture Analysis
Texture, a significant visual attribute in images, has been extensively investigated across various image recognition applications. Convolutional Neural Networks (CNNs), which have been successful in many computer vision…
AttributeObject RecognitionTexture ClassificationAn Active Learning Framework with a Class Balancing Strategy for Time Series Classification
Training machine learning models for classification tasks often requires labeling numerous samples, which is costly and time-consuming, especially in time series analysis. This research investigates Active Learning (AL) …
Active LearningClassificationFault DetectionTexture Classification+3Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis
Pooling layers (e.g., max and average) may overlook important information encoded in the spatial arrangement of pixel intensity and/or feature values. We propose a novel lacunarity pooling layer that aims to capture the …
image-classificationImage ClassificationTexture ClassificationStrideNET: Swin Transformer for Terrain Recognition with Dynamic Roughness Extraction
Advancements in deep learning are revolutionizing the classification of remote-sensing images. Transformer-based architectures, utilizing self-attention mechanisms, have emerged as alternatives to conventional convolutio…
Disaster ResponseTexture ClassificationCompositional Neural Textures
Texture plays a vital role in enhancing visual richness in both real photographs and computer-generated imagery. However, the process of editing textures often involves laborious and repetitive manual adjustments of text…
Texture ClassificationTexture Classification Network Integrating Adaptive Wavelet Transform
Graves' disease is a common condition that is diagnosed clinically by determining the smoothness of the thyroid texture and its morphology in ultrasound images. Currently, the most widely used approach for the automated …
ClassificationTexture ClassificationTexTile: A Differentiable Metric for Texture Tileability
We introduce TexTile, a novel differentiable metric to quantify the degree upon which a texture image can be concatenated with itself without introducing repeating artifacts (i.e., the tileability). Existing methods for …
Data AugmentationMetric LearningTexture ClassificationTexture SynthesisGrey Level Co-occurrence Matrix (GLCM) Based Second Order Statistics for Image Texture Analysis
Grey Level Co-occurrence Matrix and Grey Level Difference Vector are described and computed for twenty four 128 x 128 x 3 test images along horizontal, vertical and diagonal directions. Second order image statistics such…
Texture ClassificationLatent space configuration for improved generalization in supervised autoencoder neural networks
Autoencoders (AE) are simple yet powerful class of neural networks that compress data by projecting input into low-dimensional latent space (LS). Whereas LS is formed according to the loss function minimization during tr…
Texture Classification