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DBF: Dynamic Belief Fusion for Combining Multiple Object Detectors

Hyungtae Lee, Heesung Kwon
2019 IEEE Transactions on Pattern Analysis and Machine Intelligence  
In this paper, we propose a novel and highly practical score-level fusion approach called dynamic belief fusion (DBF) that directly integrates inference scores of individual detections from multiple object  ...  for the fusion.  ...  This fusion process (the probability assignment and the combination rule) is called Dynamic Belief Fusion (DBF). Figure 2 : 2 Figure 2: Flow diagram of the proposed fusion algorithm, DBF.  ... 
doi:10.1109/tpami.2019.2952847 pmid:31722478 fatcat:mj7r4wdjlfeibkkdcd4u3rcpx4

Dynamic Belief Fusion for Object Detection [article]

Hyungtae Lee, Heesung Kwon, Ryan M. Robinson, William d. Nothwang, and Amar M. Marathe
2015 arXiv   pre-print
A novel approach for the fusion of heterogeneous object detection methods is proposed.  ...  The main contribution of the proposed work is a novel fusion method, called Dynamic Belief Fusion (DBF), which dynamically assigns probabilities to hypotheses (target, non-target, intermediate state (target  ...  Conclusions A novel fusion method, referred to as Dynamic Belief Fusion (DBF), is proposed to improve upon current late fusion methods in the context of object detection.  ... 
arXiv:1511.03183v1 fatcat:5umpydybpnczlldrvzpzbozhva

Dynamic Belief Fusion for Object Detection [article]

Ryan Robinson
2015 arXiv   pre-print
The proposed fusion method, called Dynamic Belief Fusion (DBF), dynamically assigns basic probabilities to propositions (target, non-target, uncertain) based on confidence levels in the detection results  ...  A novel approach for the fusion of detection scores from disparate object detection methods is proposed.  ...  Conclusions An effective fusion method, referred to as Dynamic Belief Fusion (DBF), is proposed to integrate more accurately detection scores from multiple object detectors.  ... 
arXiv:1502.07643v3 fatcat:gf2j6mvoirenzbmujoxawqhgw4

Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification [article]

Yilun Cao and Hyungtae Lee and Heesung Kwon
2016 arXiv   pre-print
A recently introduced novel fusion approach called dynamic belief fusion (DBF) is used to fuse the detector output with the classification prior.  ...  The prior knowledge is then fused with the decisions of object detection to improve detection accuracy by mitigating false positives of an object detector that are strongly contradicted with the prior  ...  [11] called Dynamic Belief Fusion (DBF) is used to build a probabilistic fusion model.  ... 
arXiv:1610.06907v1 fatcat:pubi5cg5evboddyr27sa52t6da

Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors

Guang Chen, Hu Cao, Canbo Ye, Zhenyan Zhang, Xingbo Liu, Xuhui Mo, Zhongnan Qu, Jörg Conradt, Florian Röhrbein, Alois Knoll
2019 Frontiers in Neurorobotics  
Few works are addressing the object detection with this sensor.  ...  In this work, we propose to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies.  ...  Decision-Level Fusion Dynamic Belief Fusion (DBF) in Lee et al. (2016) is a state-ofthe-art algorithm for the fusion of heterogeneous object detection methods.  ... 
doi:10.3389/fnbot.2019.00010 pmid:31001104 pmcid:PMC6454154 fatcat:ghcpudwcjjdixny2ysjvondyx4

Simple Fusion of Object Detectors for Improved Performance and Faster Deployment

Chan-Tong Lam, Jose Gaspar, Wei Ke, Marcus Im.
2021 IEEE Access  
The improvements extend to most classes, fusion sizes, and base detector combinations, revealing AP improvements up to 17.35% over baselines, for particular object classes.  ...  We propose a Simple Fusion of Object Detectors (SFOD) late ensemble method to combine existing pre-trained, off-the-shelf, fine-tuned object detectors and leverage on their divergences to improve the overall  ...  [33] propose a novel Dynamic Belief Fusion (DBF) late fusion method to combine heterogeneous object detectors based on prior dynamic basic probability assignments (target, non-target, and intermediate  ... 
doi:10.1109/access.2021.3060768 fatcat:fpidljf3tfgjhkru6amepeefoe

Usability Evaluation Approach of Educational Resources Software Using Mixed Intelligent Optimization

Jiaze Sun
2017 Mathematical Problems in Engineering  
subjective and objective methods to measure software usability for educational resources software.  ...  problems of strong subjectivity and uncertain fuzziness of attribute weights in the software usability evaluation approach, an evaluation approach based on mixed intelligent optimization was proposed, which combines  ...  Literature [17] proposed Dynamic Belief Fusion (DBF) method to assign probabilities to individual detectors, which optimally fused information from all detectors.  ... 
doi:10.1155/2017/2926904 fatcat:pglut73njbh2lcyk6llndjhxfm

New transformed features generated by deep bottleneck extractor and a GMM–UBM classifier for speaker age and gender classification

Arafat Abu Mallouh, Zakariya Qawaqneh, Buket D. Barkana
2017 Neural computing & applications (Print)  
The highest accuracy is calculated as 72.97% for adult female speakers.  ...  In this work, a model for generating bottleneck features from a deep neural network and a Gaussian Mixture Model-Universal Background Model (GMM-UBM) classifier are proposed for speaker age and gender  ...  In addition, they combined two or more systems by using fusion technique to increase the classification accuracy.  ... 
doi:10.1007/s00521-017-2848-4 pmid:30363735 pmcid:PMC6182368 fatcat:fp5obp2ncncyhgy7q742fvmna4

Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors

Guang Chen, Hu Cao, Canbo Ye, Zhenyan Zhang, Xingbo Liu, Xuhui Mo, Zhongnan Qu, Jörg Conradt, Florian Röhrbein, Alois Knoll
2019
Few works are addressing the object detection with this sensor.  ...  In this work, we propose to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies.  ...  Decision-Level Fusion Dynamic Belief Fusion (DBF) in Lee et al. (2016) is a state-ofthe-art algorithm for the fusion of heterogeneous object detection methods.  ... 
doi:10.3929/ethz-b-000339165 fatcat:mbzxjbayazg2dko7korqoswziq

Intelligent Radio Signal Processing: A Survey [article]

Quoc-Viet Pham and Nhan Thanh Nguyen and Thien Huynh-The and Long Bao Le and Kyungchun Lee and Won-Joo Hwang
2021 arXiv   pre-print
Intelligent signal processing for wireless communications is a vital task in modern wireless systems, but it faces new challenges because of network heterogeneity, diverse service requirements, a massive  ...  This survey covers four intelligent signal processing topics for the wireless physical layer, including modulation classification, signal detection, beamforming, and channel estimation.  ...  to network dynamics.  ... 
arXiv:2008.08264v3 fatcat:4wmxyio6ejfvbfnqodq5z426m4

Intelligent Radio Signal Processing: A Survey

Quoc-Viet Pham, Nhan Thanh Nguyen, Thien Huynh-The, Long Bao Le, Kyungchun Lee, Won-Joo Hwang
2021 IEEE Access  
to network dynamics.  ...  For example, Wang et al. introduced a decision-level fusion model for processing different incoming signals received by multiple antennas in a MIMO system, where a five-layer CNN performs the function  ... 
doi:10.1109/access.2021.3087136 fatcat:lovomskphvecbnxmvbm4dadssi

2021 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 43

2022 IEEE Transactions on Pattern Analysis and Machine Intelligence  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Saragadam, V., +, TPAMI July 2021 2233-2244 Image fusion DBF: Dynamic Belief Fusion for Combining Multiple Object Detectors.  ...  Yang, W., +, TPAMI Nov. 2021 4059-4077 Detectors AP-Loss for Accurate One-Stage Object Detection.  ... 
doi:10.1109/tpami.2021.3126216 fatcat:h6bdbf2tdngefjgj76cudpoyia

W/Z properties and V+jets at the Tevatron

Darren D. Price
2012 EPJ Web of Conferences  
New measurements of jets produced in association with Z and W bosons for inclusive, beauty and charm jets are also discussed.  ...  We present a summary of recent measurements of W and Z properties and W/Z production in association with jets in pp̅ collisions at √(s)=1.96 TeV with the CDF and DØ detectors.  ...  I also thank for the conference organizers for a very rich week of physics.  ... 
doi:10.1051/epjconf/20122806006 fatcat:3672lmse6rfhjnwfobkthh26se

Image De-noising with Machine Learning: A Review

Rini Smita Thakur, Shubhojeet Chatterjee, Ram Narayan Yadav, Lalita Gupta
2021 IEEE Access  
For impulse noise removal, Blind CNN, and CNN+PSO perform well. For mixed noise removal, WDL, EM-CNN, CNN, SDL, and Mixed CNN are prominent.  ...  The best de-noising results for different noise type is discussed along with future prospects. Among various Gaussian noise de-noisers, GCBD, BRDNet and PReLU network prove to be promising.  ...  Chen et al. have proposed a Deep Boosting Framework (DBF) [93] for realworld image denoising by combining the deep learning into the boosting algorithm.  ... 
doi:10.1109/access.2021.3092425 fatcat:xirq6soukzchvaeiugcpgxnlqi

Nanophotonic Information System [chapter]

2016 Information Photonics  
This chapter also elaborates photonic instrumentations required for range acquisition and profiling of an object.  ...  In the same vein, optical computers will be termed photonic computers, the sources, detectors, and modulators shall be termed photonic detectors, photonic sources, and photonic modulators.  ... 
doi:10.1201/9781315373072-20 fatcat:4cmzaf2bvjcsvjuisyxmtanboy
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