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A two-step approach for detecting Striga in a complex agroecological system using Sentinel-2 data

Bester Tawona Mudereri, Elfatih Mohamed Adel-Rahman, Timothy Dube, Saliou Niassy, Zeyaur Khan, Henri.E.Z. Tonnang, Tobias Landmann
2020 Science of the Total Environment  
In this study, a two-step classification approach was used to detect Striga (Striga hermonthica) weed occurrence within croplands in Rongo, Kenya.  ...  The remaining cropland area was then used in a subpixel multiple endmember spectral mixture analysis (MESMA) to detect Striga occurrence and infestation using endmembers (EMs) obtained from the in-situ  ...  For each of the mapping approaches (i.e. cropland mapping in GEE and Striga occurrence mapping using MESMA), the error matrices that provided all the four metrics i.e.  ... 
doi:10.1016/j.scitotenv.2020.143151 pmid:33143922 fatcat:q43i4eznijd3hpqzd6jchrooem

A Review of Web Infodemic Analysis and Detection Trends across Multi-modalities using Deep Neural Networks [article]

Chahat Raj, Priyanka Meel
2021 arXiv   pre-print
This review primarily deals with multi-modal fake news detection techniques that include images, videos, and their combinations with text.  ...  Researchers are analyzing online data based on multiple modalities composed of text, image, video, speech, and other contributing factors.  ...  [98] used RGB color components in the images to detect changes that occurred due to tampering. Nataraj et al. [99] detected GAN-generated images using co-occurrence matrices.  ... 
arXiv:2112.00803v1 fatcat:twppg5v37bdozcdloaa6zfk7s4

Context based object categorization: A critical survey

Carolina Galleguillos, Serge Belongie
2010 Computer Vision and Image Understanding  
Recognizing an object in an image is difficult when images present occlusion, poor quality, noise or background clutter, and this task becomes even more challenging when many objects are present in the  ...  Several models for object categorization use appearance and context information from objects to improve recognition accuracy.  ...  The majority of the context-based models include at most two different types of context, semantic and spatial, since the complexity to determine scale context is still high for 2D images.  ... 
doi:10.1016/j.cviu.2010.02.004 fatcat:3ee2st4tffbnplewyrq5o4i5rm

Detection of Opinion Communities with the Help of Chance-Corrected Measures of Agreement

Anton Oleinik
2020 SN Computer Science  
It is argued that with their help it is possible to increase the accuracy of users' assessment of various items (texts, but also potentially images, movies, music and goods).  ...  Chance-corrected measures of similarity also allow for the detection of similarly minded users in a more accurate manner. Results of small-scale empirical tests inform the discussion.  ...  In the case of the image, segments refer to picture elements (pixels of certain size); in the case of the movie or video, segments refer to scenes, etc.  ... 
doi:10.1007/s42979-020-00129-8 fatcat:uzeye4qxpzcnpbyjiuj36vl3my

Pipelining Localized Semantic Features for Fine-Grained Action Recognition [chapter]

Yang Zhou, Bingbing Ni, Shuicheng Yan, Pierre Moulin, Qi Tian
2014 Lecture Notes in Computer Science  
In fine-grained action (object manipulation) recognition, it is important to encode object semantic (contextual) information, i.e., which object is being manipulated and how it is being operated.  ...  In the feature encoding stage, we develop a semantic-grouped locality-constrained linear coding (SG-LLC) method that captures the joint distributions between motion and object-in-use information.  ...  This is because in fine-grained actions, local manipulation motion details (e.g., subtle movements of hand in operating an object) are much more important than global co-occurrence information.  ... 
doi:10.1007/978-3-319-10593-2_32 fatcat:zoakjrjhsjdenos4rnnbe5u4lq

GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection [article]

João C. Neves, Ruben Tolosana, Ruben Vera-Rodriguez, Vasco Lopes, Hugo Proença, Julian Fierrez
2020 arXiv   pre-print
of this type of facial manipulation, considering the state-of-the-art fake detection systems (based on holistic deep networks, steganalysis, and local artifacts), remarking how challenging is this task  ...  detection systems while keeping the visual quality of the resulting images; ii) an in-depth analysis of the recent literature in facial manipulation detection; iii) a complete experimental assessment  ...  In particular, this approach calculates the co-occurrence matrices directly from the image pixels on each channel (red, green and blue), and passes this information through a custom CNN, which allows the  ... 
arXiv:1911.05351v4 fatcat:vleylpyukfhuxbjl724imrgn6m

Context modeling in computer vision: techniques, implications, and applications

Oge Marques, Elan Barenholtz, Vincent Charvillat
2010 Multimedia tools and applications  
The basic motivation behind these diverse efforts is generally the same-attempting to enhance current image analysis technologies by incorporating information from outside the target object, including  ...  This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context  ...  It is straightforward to build context matrices to count co-occurrence of labels given a dataset where many objects are labeled.  ... 
doi:10.1007/s11042-010-0631-y fatcat:cspmqzbtinexrghz2zxjklkyva

Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis

Ioannis Tsougos, Alexandros Vamvakas, Constantin Kappas, Ioannis Fezoulidis, Katerina Vassiou
2018 Computational and Mathematical Methods in Medicine  
Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment  ...  Furthermore, the combination with state-of-the-art image analysis methods provides a plethora of quantifiable imaging features, termed radiomics that increases diagnostic accuracy towards individualized  ...  Second-order histograms such as graylevel co-occurrence matrices (GLCMs) [28, 48] and graylevel run-length matrices (GLRLMs) [29, 49] characterize spatial relationships between pixel intensities in  ... 
doi:10.1155/2018/7417126 fatcat:z25pzfuwnzfthdf762nchgcphy

Fusion of handcrafted and deep features for forgery detection in digital images

Savita Walia, Krishan Kumar, Munish Kumar, Xiao-Zhi Gao
2021 IEEE Access  
The pixels of an image are used to determine the intrinsic changes in the images due to underlying manipulations.  ...  Due to such manipulations, the intrinsic properties of the image, such as pixel correlations, chrominance, and luminance characteristics, become inconsistent.  ... 
doi:10.1109/access.2021.3096240 fatcat:momibd4a7vaixobzqzv5bg53sm

Exemplar-Based Recognition of Human–Object Interactions

Jian-Fang Hu, Wei-Shi Zheng, Jianhuang Lai, Shaogang Gong, Tao Xiang
2016 IEEE transactions on circuits and systems for video technology (Print)  
Human action can be recognised from a single still image by modelling human-object interactions (HOI), which infers the mutual spatial structure information between human and the manipulated object as  ...  Existing approaches rely heavily on accurate detection of human and object and estimation of human pose; they are thus sensitive to large variations of human poses, occlusion and unsatisfactory detection  ...  Existing approaches focus on modelling the co-occurrence or spatial relationship between human and the manipulated object.  ... 
doi:10.1109/tcsvt.2015.2397200 fatcat:v7cusm7hcfbj5aeqrdqwrb6cq4

Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Focus on Mitochondrial DNA and Alzheimer's Disease

Annamaria Zaia, Pierluigi Maponi, Giuseppina Di Stefano, Tiziana Casoli
2017 Aging and Disease  
Fractal lacunarity analysis represents a useful tool to analyze mtDNA mutations.  ...  Therefore, Chaos Game Representation method has been used to display DNA fractal properties after adapting the algorithm to visualize also heteroplasmic mutations.  ...  They contributed to generate CGR matrices during their INRCA experience as stagers.  ... 
doi:10.14336/ad.2016.0629 pmid:28197358 pmcid:PMC5291006 fatcat:nf24hjam4rfyjeo7flkys7jdjm

A rational model of the effects of distributional information on feature learning

Joseph L. Austerweil, Thomas L. Griffiths
2011 Cognitive Psychology  
In particular, we investigate whether people are sensitive to how parts co-vary over objects they observe.  ...  In a series of four behavioral experiments (three using visual stimuli, one using conceptual stimuli), we demonstrate that people infer different features to represent the same four objects depending on  ...  structure of the stimuli: The co-occurrence of parts creates a pattern of correlation that is best explained by postulating the objects themselves as features, resulting in a holistic representation of  ... 
doi:10.1016/j.cogpsych.2011.08.002 pmid:21937008 fatcat:buoxuzp47zdg7k47ak6pbovtza

Comparative Performance Evaluation of Pixel-Level and Decision-Level Data Fusion of Landsat 8 OLI, Landsat 7 ETM+ and Sentinel-2 MSI for Crop Ensemble Classification

Juliana Useya, Shengbo Chen
2018 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
This research implements parallel and concatenation approach to ensemble classify the images.  ...  Objective of this study is to evaluate the comparative performance between decision-and pixel-levels data fusion ensemble classified maps using Landsat 8, Landsat 7, and Sentinel-2 data.  ...  Cloud and cloud shadow mask from Landsat 8 imagery are used to mask out cloud-free pixels from either reference images.  ... 
doi:10.1109/jstars.2018.2870650 fatcat:flrvhffevvfklonp65qxgd7jbq

Author Index

2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
Fuchs, Thomas Neuron Geometry Extraction by Perceptual Grouping in ssTEM Images Fujiyoshi, Hironobu Workshop: Feature Co-occurrence Representation Based on Boosting for Object Detection Furukawa  ...  Co-clustering of Image Segments Using Convex Optimization Applied to EM Neuronal Reconstruction Vitaladevuni, Shiv Increasing Depth Resolution of Electron Microscopy of Neural Circuits using Sparse Tomographic  ... 
doi:10.1109/cvpr.2010.5539913 fatcat:y6m5knstrzfyfin6jzusc42p54

Invariant Deep Compressible Covariance Pooling for Aerial Scene Categorization

Shidong Wang, Yi Ren, Gerard Parr, Yu Guan, Ling Shao
2020 IEEE Transactions on Geoscience and Remote Sensing  
We consider transforming the input image according to a finite transformation group that consists of multiple confounding orthogonal matrices, such as the D4 group.  ...  In particular, with using ResNet architecture, our IDCCP model can reduce the dimension of the tensor representation by about 98% without sacrificing accuracy (i.e., <0.5%).  ...  These methods can detect co-occurrences of features at any positions in a standard CNN architecture, and any preferred poses in a G-space, but the computational cost scales dramatically with the increasing  ... 
doi:10.1109/tgrs.2020.3026221 fatcat:254e2pou3fb3tlexrebsubtlia
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