Filters








19,214 Hits in 8.4 sec

Object detection in multi-modal images using genetic programming

Bir Bhanu, Yingqiang Lin
2004 Applied Soft Computing  
Our approach is based on genetic programming (GP).  ...  and primitive features to effectively detect objects in images and the learned composite operators can be applied to the whole training image and other similar testing images.  ...  Conclusions In this paper, we use genetic programming to synthesize composite operators and composite features to detect potential objects in images.  ... 
doi:10.1016/j.asoc.2004.01.004 fatcat:spjrwiayfvgvnfinwdicgecclq

DIAGNOSIS-GUIDED METHOD FOR IDENTIFYING MULTI-MODALITY NEUROIMAGING BIOMARKERS ASSOCIATED WITH GENETIC RISK FACTORS IN ALZHEIMER'S DISEASE

Xiaoke Hao, Jingwen Yan, Xiaohui Yao, Shannon L Risacher, Andrew J Saykin, Daoqiang Zhang, Li Shen, ADNI
2016 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
To reveal disease-relevant imaging genetic associations, we propose a novel diagnosis-guided multi-modality (DGMM) framework to discover multi-modality imaging QTs that are associated with both Alzheimer's  ...  Many recent imaging genetic studies focus on detecting the associations between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs).  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following:  ... 
pmid:26776178 pmcid:PMC4719777 fatcat:pjkrs5bw5rbd7osu75xp75thkq

DIAGNOSIS-GUIDED METHOD FOR IDENTIFYING MULTI-MODALITY NEUROIMAGING BIOMARKERS ASSOCIATED WITH GENETIC RISK FACTORS IN ALZHEIMER'S DISEASE

XIAOKE HAO, JINGWEN YAN, XIAOHUI YAO, SHANNON L. RISACHER, ANDREW J. SAYKIN, DAOQIANG ZHANG, LI SHEN
2015 Biocomputing 2016  
To reveal disease-relevant imaging genetic associations, we propose a novel diagnosis-guided multi-modality (DGMM) framework to discover multi-modality imaging QTs that are associated with both Alzheimer's  ...  Many recent imaging genetic studies focus on detecting the associations between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs).  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association  ... 
doi:10.1142/9789814749411_0011 fatcat:x7y7yv6ijbelrpjwpd23d5yioa

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease

Xiaoke Hao, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Daoqiang Zhang, Li Shen
2016 Neuroinformatics  
In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status.  ...  In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: At Indiana University, this work  ... 
doi:10.1007/s12021-016-9307-8 pmid:27277494 pmcid:PMC5010986 fatcat:z4eg6g2javf3fayicapo5y5eyu

Modern Signal Processing Techniques for GPR Applications

M. Mostafa, Fathy Ahmed, Aly Attallah
2017 International Conference on Aerospace Sciences and Aviation Technology  
This paper introduces a survey of different modern signal processing techniques used in the ground penetrating radar (GPR) for an ongoing research regarding buried objects detection.  ...  In GPR, microwaves signals are transmitted until an object reflects them back, then the reflected signals are processed in order to extract information about the target.  ...  The objective is to detect, locate and identify a buried object in GPR image.  ... 
doi:10.21608/asat.2017.22383 fatcat:vyamts2mbrd7feafpr4v7fmk54

Deep Principal Correlated Auto-encoders With Application to imaging and Genomics Data Integration

Gang Li, Chao Wang, De-Peng Han, Yi-Pu Zhang, Peng Peng, Vince D. Calhoun, Yu-Ping Wang
2020 IEEE Access  
In terms of complex diseases like schizophrenia, more and more studies are beginning to treat genetic variants and brain imaging phenotypes as an important factor.  ...  Many existing advanced models had been developed to find the maximal correlation in multi-modality data.  ...  imaging genetic data.  ... 
doi:10.1109/access.2020.2968634 fatcat:pcvqm2edkbhkfmz6qhbnbxwkai

Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges [article]

Di Feng, Christian Haase-Schuetz, Lars Rosenbaum, Heinz Hertlein, Claudius Glaeser, Fabian Timm, Werner Wiesbeck, Klaus Dietmayer
2020 arXiv   pre-print
This review paper attempts to systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving.  ...  In this context, many methods have been proposed for deep multi-modal perception problems.  ...  Deep Multi-modal Semantic Segmentation Compared to the object detection problem summarized in Sec.  ... 
arXiv:1902.07830v4 fatcat:or6enjxktnamdmh2yekejjr4re

There is no data like more data – current status of machine learning datasets in remote sensing [article]

Michael Schmitt, Seyed Ali Ahmadi, Ronny Hänsch
2021 arXiv   pre-print
In this paper, we review the historic development of such datasets, discuss their features based on a few selected examples, and address open issues for future developments.  ...  When it comes to data volume, however, semantic segmentation and classification lead the way, which indicates that in contrast to object detection here more multi-modal data are used. • As of the time  ...  Instead of just focusing on object detection or scene classification, a multi-use annotation would enhance re-usability significantly. • Since manual labeling of large amounts of remote sensing imagery  ... 
arXiv:2105.11726v2 fatcat:mcpwl3a2y5cl5jl5m2llyxu4ni

Front Matter: Volume 9443

2015 Sixth International Conference on Graphic and Image Processing (ICGIP 2014)  
The papers included in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee.  ...  SPIE uses a six-digit CID article numbering system in which: The first four digits correspond to the SPIE volume number.  ...  We hope you had a unique, rewarding, and enjoyable weekend at ICGIP 2014 in Beijing, China. Yulin Wang xvi Proc. of SPIE Vol. 9443 944301-16  ... 
doi:10.1117/12.2190588 fatcat:rkjeosz2jjcunie2ibugkatcae

An evolutionary-based image classification approach through the facial attributes

2020 Turkish Journal of Electrical Engineering and Computer Sciences  
In this study, we have proposed an evolutionary-based framework 8 that relies on genetic programming algorithm to evolve a binary-and multi-label image classifier program for gender 9 classification, facial  ...  algorithm (GA) [9], genetic programming 3 (GP) [10, 11], grammatical evolution (GE) [12], and the like.  ...  Malware detection using genetic programming.  ... 
doi:10.3906/elk-2003-75 fatcat:k7u3wairovfq5gitendvmycxba

Guest Editorial: Evolutionary Computation for Image Processing

2020 IET Image Processing  
By adding semantic segmentation branches to the target detection network, the authors innovatively realise the multi vision task of object classification, detection and semantic segmentation.  ...  Kullback-Leibler single shot multibox detection (KSSD) object detection algorithm is proposed to improve the accuracy of small-and medium-sized object detection.  ... 
doi:10.1049/iet-ipr.2020.1284 fatcat:7hyc6zbjurc3ffxsraw7fu6qru

High Performance Adaptive Fidelity Algorithms for Multi-Modality Optic Nerve Head Image Fusion

Hua Cao, Nathan Brener, Bahram Khoobehi, S. Sitharama Iyengar
2010 Journal of Signal Processing Systems  
A high performance adaptive fidelity approach for multi-modality Optic Nerve Head (ONH) image fusion is presented.  ...  In addition, the performance of the AFEA and HOA algorithms was compared to the Centerline Control Point Detection Algorithm, Root Mean Square Error (RMSE) minimization objective function employed by the  ...  This work is funded by BCVC programs.  ... 
doi:10.1007/s11265-010-0496-3 fatcat:dgnforkr7jbnzan5krs7fgndf4

Integration of Behavioral, Structural, Functional, and Genetic Data for the Study of Autism Spectrum Disorders [chapter]

Carinna M. Torgerson, Andrei Irimia, S.-Y. Matthew Goh, John D. Van Horn
2015 Lecture Notes in Computer Science  
As the designated Data Coordinating Center in the Autism Center of Excellence (ACE) network, the Laboratory of Neuro Imaging (LONI) is faced with the task of efficiently organizing data from behavioral  ...  users to create workflows by mixing and matching analytic tools from a library of common neuroimaging, genetics, and statistical software packages.  ...  By combining a massive multi-modal database and a processing environment which can handle a wide variety of data types, our project has aimed to make data integration the least difficult component of multi-modal  ... 
doi:10.1007/978-3-319-21843-4_16 fatcat:xrnjaazuhrdbfcnvcorfjlsxwi

MultiBiometric Fusion: Left and Right Irises based Authentication Technique

Leila Zoubida, Réda Adjoudj
2017 International Journal of Image Graphics and Signal Processing  
There are several modalities used in the biometric applications, among these different traits we choose the iris modality.  ...  The obtained results have confirmed that the multi-biometric systems are better than the mono-modal systems according to their performance.  ...  Image, Graphics and Signal Processing, 2017, 4, 10-21 (5) . Multi-modal system: In this system, there are several traits biometric acquired by the different sensors.  ... 
doi:10.5815/ijigsp.2017.04.02 fatcat:2oesp6t4jjb3tmg4ndgi6yp5cm

RECOD at ImageCLEF 2011: Medical Modality Classification using Genetic Programming

Fábio Augusto Faria, Rodrigo Tripodi Calumby, Ricardo da Silva Torres
2011 Conference and Labs of the Evaluation Forum  
We present an approach based on genetic programming and kNN for image classification.  ...  In our approach the genetic programming is used for the learning of good functions for the combination of similarities obtained from a set of global descriptors for different visual evidences such as color  ...  Section 3 presents our proposed approach for image classification using genetic programming.  ... 
dblp:conf/clef/FariaCT11 fatcat:artrvi3ydfhkxpctmgwnzstwr4
« Previous Showing results 1 — 15 out of 19,214 results