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Commuting Conditional GANs for Robust Multi-Modal Fusion [article]

Siddharth Roheda, Hamid Krim, Benjamin S. Riggan
2019 arXiv   pre-print
This paper presents a data driven approach to multi-modal fusion, where optimal features for each sensor are selected from a common hidden space between the different modalities.  ...  In [14] where a Conditional Generative Adversarial Network (CGAN) was used to generate representative features for the missing modality.  ...  The blue plot represents the negative of the discriminator loss for the GAN network (y-axis on left), while the orange plot corresponds to the commutation loss (y-axis on right).  ... 
arXiv:1906.04115v2 fatcat:tfki5znknncelpgvczenkcck3u

Traffic Flow Online Prediction Based on a Generative Adversarial Network with Multi-Source Data

Tuo Sun, Bo Sun, Zehao Jiang, Ruochen Hao, Jiemin Xie
2021 Sustainability  
Multi-dimensional indicators are selected to map the multi-view fusion local trend for accurate prediction.  ...  In comparison with the autoregressive integrated moving average (ARIMA), BiLSTM, generating adversarial network for traffic flow (GAN-TF), and generating adversarial network for non-signal traffic (GAN-NST  ...  Traffic flow is determined by modal split and routine choice influenced by many factors, including daily commuting and non-commuting activities, holidays, weather, public activities, traffic events, urban  ... 
doi:10.3390/su132112188 fatcat:npfekq4agzfwfj74ni4lxq2twa

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders [article]

Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
2019 arXiv   pre-print
The key to our approach is that we align the distributions learned from images and from side-information to construct latent features that contain the essential multi-modal information associated with  ...  Many approaches in generalized zero-shot learning rely on cross-modal mapping between the image feature space and the class embedding space.  ...  These approaches treat GZSL as a missing data problem and train conditional GANs or conditional VAEs to generate image features for unseen classes from semantic side-information.  ... 
arXiv:1812.01784v4 fatcat:px7zvsnsz5a5zfxt7vbvhxnh54

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization [article]

Jin Li, Wanyun Li, Zichen Xu, Yuhao Wang, Qiegen Liu
2021 arXiv   pre-print
By taking advantage of the multi-scale and multi-channel representation via wavelet transform, the proposed model learns the priors from stacked wavelet coefficient components, thus learns the image characteristics  ...  Specifically, in the training phase, a set of multi-channel tensors consisting of wavelet coefficients are used as the input to train the network by denoising score matching.  ...  As the colorization problem requires a mapping from one-channel grayscale image to multi-channel composite image, it is essentially ill-conditioned and ambiguous with multi-modal uncertainty.  ... 
arXiv:2107.04261v1 fatcat:f2vwnyxyrvcoxaax6mcxhxhkoy

IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications

Zhanyu Ma, Sunwoo Kim, Pascual Martinez-Gomez, Jalil Taghia, Yi-Zhe Song, Huiji Gao
2020 IEEE Access  
City-scale traffic speed prediction provides a significant data foundation for intelligent transportation systems, which enrich commuters with up-to-date information about traffic conditions.  ...  The selection of semantic concepts for modal construction and data collection remains an open research issue.  ...  The authors present a multi-scale adjacent connection module (ACM) to provide effective contextual information and reduce interference for vehicle detection.  ... 
doi:10.1109/access.2020.3035461 fatcat:rt7ejtponrfexigie4cfpt7gd4

Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization [article]

Maysam Behmanesh, Peyman Adibi, Jocelyn Chanussot, Sayyed Mohammad Saeed Ehsani
2021 arXiv   pre-print
correspondences between modalities are determined based on the FMBSD method.  ...  Most of these methods work based on two major assumptions: 1) there are the same number of homogeneous data samples in each modality, and 2) at least partial correspondences between modalities are given  ...  Multimodal manifold learning is an important category of multimodal learning methods that extends spectral or geometry-aware data analysis techniques for information fusion given multiple modalities.  ... 
arXiv:2105.05631v1 fatcat:64uqblnzb5btnnhkeuzortajtq

Miniaturized optogenetic neural implants: a review

B. Fan, W. Li
2015 Lab on a Chip  
This article reviews recent developments in miniaturized neural implants for optogenetics, highlights major improvements enabled by microtechnologies, and discusses challenges faced by developers and adopters  ...  fiber optics, tethers, and commutators.  ...  commutators, and may bias the outcomes 61 .  ... 
doi:10.1039/c5lc00588d pmid:26308721 fatcat:uzxxnvfhizgypn6ub3yfy2acmy

Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey [article]

Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Erik Cambria
2022 arXiv   pre-print
Furthermore, we comprehensively review the evaluation methods and datasets for dialogue systems to pave the way for future research.  ...  We speculate that this work is a good starting point for academics who are new to the dialogue systems or those who want to quickly grasp up-to-date techniques in this area.  ...  Gan et al. (2019) performed multi-step reasoning conditioned on a dialogue history memory module and a visual memory module.  ... 
arXiv:2105.04387v5 fatcat:yd3gqg45rjgzxbiwfdlcvf3pye

A Gentle Introduction to Deep Learning in Medical Image Processing [article]

Andreas Maier, Christopher Syben, Tobias Lasser, Christian Riess
2018 arXiv   pre-print
Doing so allows us to understand the reasons for the rise of deep learning in many application domains.  ...  We first discuss general reasons for the popularity of deep learning, including several major breakthroughs in computer science.  ...  Furthermore, we would like to thank Florin Ghesu, Bastian Bier, Yixing Huang, and again Katharina Breininger for the permission to highlight their work and images in this introduction. Last  ... 
arXiv:1810.05401v2 fatcat:dtd5eyj65jbfdjtsywxw3ilaqq

Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research [article]

Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Rada Mihalcea
2020 arXiv   pre-print
We analyze the significant leaps responsible for its current relevance. Further, we attempt to chart a possible course for this field that covers many overlooked and unanswered questions.  ...  -A19E2b0098, Project name -K-EMERGE: Knowledge Extraction, Modelling, and Explainable Reasoning for General Expertise.  ...  Fine-Grained Annotation The primary goal of multimodal fusion is to accumulate the contribution from each modality.  ... 
arXiv:2005.00357v5 fatcat:gjzglyhtvvc3xnuaeqjocbp57u

A Metaverse: taxonomy, components, applications, and open challenges

Sang-Min Park, Young-Gab Kim
2022 IEEE Access  
Finally, we summarize the limitations and directions for implementing the immersive Metaverse as social influences, constraints, and open challenges.  ...  The integration of enhanced social activities and neural-net methods requires a new definition of Metaverse suitable for the present, different from the previous Metaverse.  ...  Personal Dialog is a large multi-rotational dialogue dataset based on sequential conditional GANs containing different characteristics of different speakers (e.g., age, gender, location, interest tags)  ... 
doi:10.1109/access.2021.3140175 fatcat:fnraeaz74vh33knfvhzrynesli

2021 Index IEEE Transactions on Power Delivery Vol. 36

2021 IEEE Transactions on Power Delivery  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Fusion Single Shot Multibox Detector.  ...  ., +, TPWRD Dec. 2021 3371-3382 Commutation A Novel Phase-Locked Loop for Mitigating the Subsequent Commutation Failures of LCC-HVDC Systems.  ... 
doi:10.1109/tpwrd.2021.3134378 fatcat:j6k564co6rgxlpbupmrvns35ui

2019-2020 Index IEEE Transactions on Industrial Electronics Vol. 67

2020 IEEE transactions on industrial electronics (1982. Print)  
., Energy-Efficient Supplemental LED Lighting Control for a Proof-of-Concept Greenhouse System; TIE April 2020 3033-3042 Jiang, J., see Ma, J., TIE July 2020 5687-5695 Jiang, J., see Wang, J., TIE Aug.  ...  2020 6864-6873 Jiang, J., see Wang, D., TIE Dec. 2020 10833-10843 Jiang, J., see Zhang, X., TIE May 2020 3840-3849 Jiang, K., Yan, F., and Zhang, H., Hydrothermal Aging Factor Estimation for Two-Cell  ...  ., +, TIE Aug. 2020 6407-6417 Analysis and Design of a 1-MHz Bidirectional Multi-CLLC Resonant DC-DC Converter With GaN Devices.  ... 
doi:10.1109/tie.2020.3045338 fatcat:gljm7ngg3fakvmnfswcbb5vwiu

Deep Learning Aided Data-Driven Fault Diagnosis of Rotatory Machine: A Comprehensive Review

Shiza Mushtaq, M. M. Manjurul Islam, Muhammad Sohaib
2021 Energies  
In this review paper, various signal processing techniques, classical machine learning approaches, and deep learning algorithms used for bearing fault diagnosis have been discussed.  ...  deep convolutional network (CNN), auto-encoder-based deep neural network (AE-DNN), deep belief network (DBN), deep recurrent neural network (RNN), and other deep learning methods that have been utilized for  ...  In [49] , a multi-sensor feature fusion method for fault bearing diagnosis with SAE and DBN methods combination was proposed.  ... 
doi:10.3390/en14165150 fatcat:vfjiv6qryzgi3pyg3zthyzdtei

2020 Index IEEE Photonics Journal Vol. 12

2020 IEEE Photonics Journal  
Wang, Z., +, JPHOT June 2020 4800410 Propagation Operator Based Boundary Condition for Finite Element Analysis.  ...  Jiang, Z., +, JPHOT Dec. 2020 6901712 Propagation Operator Based Boundary Condition for Finite Element Analy- sis.  ...  Light interferometry Fourier and Inverse Fourier Transform Model for Delayed Self-interferometry System. Zhang  ... 
doi:10.1109/jphot.2021.3050278 fatcat:lbfms2rznnhurdanu5rfora5pe
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