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Showing 1-25 of 2,429 resultsfor "Index Terms":Early Fusion
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Multi-Sensor Multi-Stream Data Fusion Using Deep Learning for Hyperspectral Point Cloud Segmentation
Ahmed Jamal Afifi;Aldino Rizaldy;Elias Arbash;Sandra Lorenz;Richard Gloaguen;Michael Heizmann
2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Year: 2024 | Conference Paper |
In this paper, we explore various sensor fusion techniques for the deep learning segmentation of hyperspectral point clouds. Specifically, we trained a Residual Multi-Layer Perceptron (Res-MLP) model using early, intermediate, and late fusion strategies to enhance segmentation performance. By leveraging the rich spectral information in hyperspectral data acquired using multiple sensors, sensor fus...Show More
Research on Power Security Control Technology Based on Multimode Data Fusion
2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)
Year: 2024 | Conference Paper |
Power grid operation, equipment maintenance, construction and other power grid field operations, the task is heavy, many points and wide. There are many dangerous factors in the process of power grid operation, including human factors, environmental factors, equipment factors, management factors and other influencing factors. Aiming at the problems of single mode and complex factor, a multi-mode f...Show More
Architectural framework for Multi sensor Data fusion and validation in IoT Based system
2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
The IoT Based system is expected to be a tipping point for many applications such as Aircraft, Medical diagnosis, Autonomous systems, Military and defense services. Over the past few years, IoT based applications are witnessing the results of multiple sensors, which plays a vital role in decision making. The proposed work suggests the layered architectural framework and guidelines for modeling mul...Show More
On the duality of specific early and late fusion strategies
17th International Conference on Information Fusion (FUSION)
Year: 2014 | Conference Paper |
Cited by: Papers (2)
In this paper, we prove that specific early and specific late fusion strategies are interchangeable. In the case of the late fusion, we consider not only linear but also nonlinear combinations of scores. Our findings are important from both theoretical and practical (applied) perspectives. The duality of specific fusion strategies also answers the question why in the literature the experimental re...Show More
Summarize of multi-sensor information fusion technology for USV colony
2022 International Conference on Cloud Computing, Big Data and Internet of Things (3CBIT)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
It has gained much attention since the birth of multi-source information fusion technology for its excellent overall system performance. This paper introduces the principle of multi-source information fusion and extends the model structure of target fusion, the fusion methods and practice problems such as target detection fusion, target position fusion, target identification fusion, STA and sensor...Show More
Meteorological Disaster Monitoring and Early Warning System Design of Civil Aviation Industry Based on Data Fusion Method
2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology (ICCASIT
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Meteorological disasters are one of the major natural disasters threatening the flight safety of civil aviation. This paper proposes a civil aviation meteorological disaster monitoring and early warning system based on fusion data method. The data processing layer of the system supports the data fusion and mining functions. The study shows that finding the correction between data helps identify ke...
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Show MoreDecoupled Deep Reinforcement Learning with Sensor Fusion and Imitation Learning for Autonomous Driving Optimization
2024 6th International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Year: 2024 | Conference Paper |
Our study explores the integration of decoupled deep reinforcement learning (DRL) frameworks in autonomous driving, focusing on the impact of sensor fusion and imitation learning (IL) to enhance performance in complex, multi-task environments. Traditional DRL approaches often encounter limitations in real-time decision-making, particularly in the simultaneous handling of perception and control tas...Show More
A Comprehensive Review on Deep Learning-Based Data Fusion
Mazhar Hussain;Mattias O’Nils;Jan Lundgren;Seyed Jalaleddin Mousavirad
The rapid progress in sensor technology and computational capabilities has significantly improved real-time data collection, enabling precise monitoring of various phenomena and industrial processes. However, the volume and complexity of heterogeneous data present substantial processing challenges. Traditional data-processing techniques, such as data aggregation, filtering, and statistical analysi...Show More
Study of objective evaluation of natural colour image fusion
2012 15th International Conference on Information Fusion
Year: 2012 | Conference Paper |
This paper presents the results of an investigation into objective evaluation of natural colour image fusion. Preserving true colour information is vital for natural appearance of fused images and measures of fusion success should take this into account either within their overall fusion performance or in explicit naturalness measures. We adopt the well known gradient based objective fusion evalua...Show More
Fault Risk Early Warning Method of Distribution Network Based on Multi-source Information Fusion
2022 9th International Forum on Electrical Engineering and Automation (IFEEA)
Year: 2022 | Conference Paper |
Based on the multi-source information fusion technology, an early warning method of distribution network fault risk is designed in this paper. The distribution network fault risk characteristics of multi-source information are collected. The DS fusion theory is applied to fuse and process the distribution network fault risk characteristics to obtain a fault risk diagnosis decision. The fault risk ...Show More
An Early Gastric Cancer Detection Method Based on DETR Multi-scale Feature Fusion
2024 43rd Chinese Control Conference (CCC)
Year: 2024 | Conference Paper |
At present, the incidence and mortality of gastric cancer rank in the top five of all cancers, which seriously endangers people’s life and health, and the detection of early gastric cancer can greatly improve the survival rate of gastric cancer patients. Based on the features of early gastric cancer in gastroscopy, this paper studies the intelligent detection of early gastric cancer by using objec...Show More
Multilevel Sensor Fusion With Deep Learning
Valentin Vielzeuf;Alexis Lechervy;Stéphane Pateux;Frédéric Jurie
In the context of deep learning, this article presents an original deep network, namely CentralNet, for the fusion of information coming from different sensors. This approach is designed to efficiently and automatically balance the tradeoff between early and late fusion (i.e., between the fusion of low-level versus high-level information). More specifically, at each level of abstraction—the differ...Show More
Research on Remote Monitoring and Early Warning System of New Energy Station Based on Multi-source Information Fusion
2021 6th Asia Conference on Power and Electrical Engineering (ACPEE)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
For the data monitoring and fault early warning of new energy grid connection, the equipment status data, Supervisory Control And Data Acquisition (SCADA) system data, Wide Area Measurement System (WAMS) system data and other multi-source complex data were synchronized into the remote monitoring and early warning system of new energy station. The multi-source information fusion technology was used...Show More
Affect recognition from face and body: early fusion vs. late fusion
2005 IEEE International Conference on Systems, Man and Cybernetics
Year: 2005 | Conference Paper |
Cited by: Papers (95)
This paper presents an approach to automatic visual emotion recognition from two modalities: face and body. Firstly, individual classifiers are trained from individual modalities. Secondly, we fuse facial expression and affective body gesture information first at a feature-level, in which the data from both modalities are combined before classification, and later at a decision-level, in which we i...Show More
Early and Late Fusion Methods for the Automatic Creation of Twitter Lists
2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Year: 2012 | Conference Paper |
Twitter's list feature allows users to organize their followees into groups for easier information access and filtering. However, the percentage of users using lists is very small and most existing lists have only a few members. One reason for this may be that curating groups of Twitter users is a time consuming task. In this paper, we propose early and late fusion methods for automatically cluste...Show More
Early vs. Late Multimodal Fusion for Recognizing Confusion in Collaborative Tasks
2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Year: 2023 | Conference Paper |
There has been a rapid transformation in the medium of learning and communication due to the pandemic. Multitudes have adopted online video platforms to learn and work from any corner of the world. Emotion detection is vital for understanding how well instructions are communicated through online interactions and for building cognitive systems that can identify human behavior. Confusion is a key em...Show More
Accurate Hand Gesture Recognition Using Color and Depth Images with Modality-invariant Fusion
Masaya Okano;Jia-Qing Liu;Tomoko Tateyama;Yutaro Iwamoto;Yen-Wei Chen
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
Gesture recognition is actively used, and has been applied in various fields, including games and medicine. For accurate gesture recognition, multi-modal information with color and depth images has recently been used. In multimodal gesture recognition, the fusion of color and depth images is crucial. To date, early and late fusion approaches have been widely used for the fusion of color and depth ...Show More
Perception System based on Cooperative Fusion of Lidar and Cameras
2022 IEEE Sensors
Year: 2022 | Conference Paper |
This paper proposes a novel sensor fusion method capable of detection and tracking of road users under nominal as well as in border cases of system operation. The proposed method is based on a sensor-agnostic Bayesian late fusion framework, augmented with an optional exchange of detector activation information between sensors, referred to as cooperative feedback. Experimental evaluation confirms t...Show More
Fusion of thermal and visible images for day/night moving objects detection
2014 Sensor Signal Processing for Defence (SSPD)
Year: 2014 | Conference Paper |
Cited by: Papers (7)
A background subtraction (BS) technique based on the fusion of thermal and visible imagery using Gaussian mixture models (GMM) is presented in this work. An automatic daytime/night-time detection is introduced that can be used to dynamically adapting the fusion scheme. Three fusion schemes are investigated and coined as early, late and image fusion. The first consists in augmenting the GMM model w...Show More
Multimodal fusion frameworks for Human Action Recognition (HAR) using depth and inertial sensor data have been proposed over the years. In most of the existing works, fusion is performed at a single level (feature level or decision level), missing the opportunity to fuse rich mid-level features necessary for better classification. To address this shortcoming, in this paper, we propose three novel ...Show More
Study of statistical robust closed set speaker identification with feature and score-based fusion
Musab T. S. Al-Kaltakchi;Wai L. Woo;Satnam S. Dlay;Jonathon A. Chambers
2016 IEEE Statistical Signal Processing Workshop (SSP)
Year: 2016 | Conference Paper |
Cited by: Papers (8)
In this paper, the statistical combination of Power Normalization Cepstral Coefficient (PNCC) and Mel Frequency Cepstral Coefficient (MFCC) features in robust closed set speaker identification is studied. Feature normalization and warping together with late score-based fusion are also exploited to improve performance in the presence of channel and noise effects. In addition, combinations of score ...Show More
Video Shot Segmentation Using Late Fusion Technique
2008 Seventh International Conference on Machine Learning and Applications
Year: 2008 | Conference Paper |
Cited by: Papers (9)
In this paper, a new method for detecting shot boundaries in video sequences using a late fusion technique is proposed. The method uses color histogram as the feature, and processes each bin separately for detecting shot boundaries. The decisions from individual bins are combined later for hypothesizing the presence of shot boundaries. The method provides a certain degree of robustness against ill...Show More
Combining multi-parametric MR images for the detection of epileptogenic lesions
Meriem El Azami;Romain Bouet;Julien Jung;Alexander Hammers;Carole Lartizien
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
Year: 2015 | Conference Paper |
Detecting epileptogenic brain lesions in patients with intractable epilepsy is important as patients may then be eligible for surgery. We compared two methods of anomaly detection via combining multi-parametric MR images. The early fusion approach consists in building a single global model; in the late fusion approach three local models are constructed based each on a single MR sequence, and their...Show More
Combine Early and Late Fusion Together: A Hybrid Fusion Framework for Image-Text Matching
2021 IEEE International Conference on Multimedia and Expo (ICME)
Year: 2021 | Conference Paper |
Cited by: Papers (5)
Image-text matching is a challenging task in cross-modal learning due to the discrepancy of data representation be-tween different modalities of images and texts. The main-stream methods adopt the late fusion to generate image-text similarity on encoded cross-modal features, and put effort to capture intra-modality associations with considerably high training cost. In this work, we propose to Comb...Show More
Various types of sensors can be used for human activity recognition (HAR), and each of them has different strengths and weaknesses. Sometimes, a single sensor cannot fully observe the user’s motions from its perspective, which causes wrong predictions. While sensor fusion provides more information for HAR, it comes with many inherent drawbacks, such as user privacy and acceptance, costly setup, op...Show More
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