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Papers Texture Classification

“Texture Classification” 태그가 달린 논문 206편 · 필터 해제

Debiased Self-Training for Semi-Supervised Learning

2022-02-15 · Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan 외

Deep neural networks achieve remarkable performances on a wide range of tasks with the aid of large-scale labeled datasets. Yet these datasets are time-consuming and labor-exhaustive to obtain on realistic tasks. To miti…

Object RecognitionScene ClassificationSemi-Supervised Image ClassificationTexture Classification

Encoding Spatial Distribution of Convolutional Features for Texture Representation

2021-12-01 · NeurIPS 2021 12 · Yong Xu, Feng Li, Zhile Chen, Jinxiu Liang 외

Existing convolutional neural networks (CNNs) often use global average pooling (GAP) to aggregate feature maps into a single representation. However, GAP cannot well characterize complex distributive patterns of spatial …

Material RecognitionRetrievalTexture Classification

Segmentation of Lung Tumor from CT Images using Deep Supervision

2021-11-17 · Farhanaz Farheen, Md. Salman Shamil, Nabil Ibtehaz, M. Sohel Rahman

Lung cancer is a leading cause of death in most countries of the world. Since prompt diagnosis of tumors can allow oncologists to discern their nature, type and the mode of treatment, tumor detection and segmentation fro…

SegmentationTexture ClassificationTumor Segmentation

Data-driven and Automatic Surface Texture Analysis Using Persistent Homology

2021-10-19 · Melih C. Yesilli, Firas A. Khasawneh

Surface roughness plays an important role in analyzing engineering surfaces. It quantifies the surface topography and can be used to determine whether the resulting surface finish is acceptable or not. Nevertheless, whil…

Texture ClassificationTopological Data Analysis

VisGraphNet: a complex network interpretation of convolutional neural features

2021-08-27 · Joao B. Florindo, Young-Sup Lee, Kyungkoo Jun, Gwanggil Jeon 외

Here we propose and investigate the use of visibility graphs to model the feature map of a neural network. The model, initially devised for studies on complex networks, is employed here for the classification of texture …

ClassificationNetwork InterpretationTexture Classification

Fractal measures of image local features: an application to texture recognition

2021-08-27 · Pedro M. Silva, Joao B. Florindo

Here we propose a new method for the classification of texture images combining fractal measures (fractal dimension, multifractal spectrum and lacunarity) with local binary patterns. More specifically we compute the box …

ClassificationTexture Classification

Inference via Sparse Coding in a Hierarchical Vision Model

2021-08-03 · Joshua Bowren, Luis Sanchez-Giraldo, Odelia Schwartz

Sparse coding has been incorporated in models of the visual cortex for its computational advantages and connection to biology. But how the level of sparsity contributes to performance on visual tasks is not well understo…

image-classificationImage ClassificationSensitivityTexture Classification

Fusion of Complex Networks-based Global and Local Features for Texture Classification

2021-06-20 · Zhengrui Huang

To realize accurate texture classification, this article proposes a complex networks (CN)-based multi-feature fusion method to recognize texture images. Specifically, we propose two feature extractors to detect the globa…

Texture Classification

Machine Learning Based Texture Analysis of Patella from X-Rays for Detecting Patellofemoral Osteoarthritis

2021-06-03 · Neslihan Bayramoglu, Miika T. Nieminen, Simo Saarakkala

Objective is to assess the ability of texture features for detecting radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs. We used lateral view knee radiographs from MOST public use datase…

BIG-bench Machine LearningTexture Classification

CN-LBP: Complex Networks-based Local Binary Patterns for Texture Classification

2021-05-14 · Zhengrui Huang

To overcome the limitations of original local binary patterns (LBP), this article proposes a new texture descriptor aided by complex networks (CN) and LBP, named CN-LBP. Specifically, we first abstract a texture image (T…

ClusteringTexture Classification

A Lossless Intra Reference Block Recompression Scheme for Bandwidth Reduction in HEVC-IBC

2021-04-05 · Jiyuan Hu, Jun Wang, Guangyu Zhong, Jian Cao 외

The reference frame memory accesses in inter prediction result in high DRAM bandwidth requirement and power consumption. This problem is more intensive by the adoption of intra block copy (IBC), a new coding tool in the …

PredictionTexture Classification

Continuous monitoring of plant sub-cellular structural changes for plant and crop diseases detection by use of Intelligent Laser Speckle Classification (AI) technique

2021-03-23 · Ahmet Orun

The continuous online monitoring of early signs of plant and crop diseases, at their early stages before a potential spread, is of high importance and necessitates multi-disciplinary techniques. Within this study a propo…

Texture Classification

Unsupervised Doppler Radar-Based Activity Recognition for e-Healthcare

2021-03-18 · Yordanka Karayaneva, Sara Sharifzadeh, Wenda Li, Yanguo Jing 외

Passive radio frequency (RF) sensing and monitoring of human daily activities in elderly care homes is an emerging topic. Micro-Doppler radars are an appealing solution considering their non-intrusiveness, deep penetrati…

Activity RecognitionTexture Classification

Texture-aware Video Frame Interpolation

2021-02-26 · Duolikun Danier, David Bull

Temporal interpolation has the potential to be a powerful tool for video compression. Existing methods for frame interpolation do not discriminate between video textures and generally invoke a single general model capabl…

Texture ClassificationVideo CompressionVideo Frame Interpolation

Identifying the Origin of Finger Vein Samples Using Texture Descriptors

2021-02-08 · Babak Maser, Andreas Uhl

Identifying the origin of a sample image in biometric systems can be beneficial for data authentication in case of attacks against the system and for initiating sensor-specific processing pipelines in sensor-heterogeneou…

ClassificationGeneral ClassificationTexture Classification

Smile and Laugh Expressions Detection Based on Local Minimum Key Points

2021-01-06 · Mina Mohammadi Dashti, Majid Harouni

In this paper, a smile and laugh facial expression is presented based on dimension reduction and description process of the key points. The paper has two main objectives; the first is to extract the local critical points…

Dimensionality ReductionTexture Classification

Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery

2021-01-06 · Sarah Walker, Joshua Peeples, Jeff Dale, James Keller 외

In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) (arXiv:1602.04938) and divergence measures to analyze what changes lead to improveme…

ClassificationGeneral ClassificationSensitivityTexture Classification

Riemannian information gradient methods for the parameter estimation of ECD: Some applications in image processing

2020-11-05 · Jialun Zhou, Salem Said, Yannick Berthoumieu

Elliptically-contoured distributions (ECD) play a significant role, in computer vision, image processing, radar, and biomedical signal processing. Maximum likelihood. estimation (MLE) of ECD leads to a system of non-line…

Colorizationparameter estimationTexture Classification

Spatio-temporal encoding improves neuromorphic tactile texture classification

2020-10-27 · Anupam K. Gupta, Andrei Nakagawa, Nathan F. Lepora, Nitish V. Thakor

With the increase in interest in deployment of robots in unstructured environments to work alongside humans, the development of human-like sense of touch for robots becomes important. In this work, we implement a multi-c…

ClassificationGeneral ClassificationTexture Classification

Enhancing Haptic Distinguishability of Surface Materials with Boosting Technique

2020-10-05 · Priyadarshini K, Subhasis Chaudhuri

Discriminative features are crucial for several learning applications, such as object detection and classification. Neural networks are extensively used for extracting discriminative features of images and speech signals…

ClusteringGeneral Classificationobject-detectionObject Detection+1
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