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Wavelets in the Deep Learning Era

Zaccharie Ramzi, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu
2021 2020 28th European Signal Processing Conference (EUSIPCO)   unpublished
While the many stages of non-linearity are intrinsic to deep learning, the usage of learning with training data could also be exploited by sparsity based approaches.  ...  In particular, U-nets have proven to be extremely effective.  ...  WAVELETS IN THE DEEP LEARNING ERA Zaccharie Ramzi * † ‡ , Jean-Luc Starck * , Thomas Moreau † , Philippe Ciuciu † ‡ I.  ... 
doi:10.23919/eusipco47968.2020.9287317 fatcat:aazveprppbhalhuw57qwnqghku

A Hybrid Deep Learning Framework for Longterm Traffic Flow Prediction

Yiqun Li, Songjian Chai, Zhengwei Ma, Guibian Wang
2021 IEEE Access  
Therefore, in this paper, we proposed a hybrid deep learning model based on wavelet decomposition, convolutional neural network-long and shortterm memory neural network (CNN-LSTM), called W-CNN-LSTM, to  ...  The decomposed sequences are fed into a CNN-LSTM deep learning model, where the long-term temporal features of traffic flow can be well captured and learned.  ...  THE PROPOSED HYBRID DEEP LEARNING FRAMEWORK In this section, a hybrid day-ahead traffic flow forecasting deep learning framework, which comprises the wavelet decomposition and CNN-LSTM model, was formulated  ... 
doi:10.1109/access.2021.3050836 fatcat:bs4b3oqh2bhqtky57yj4kmrv34

On Arrhythmia Detection by Deep Learning and Multidimensional Representation [article]

K.S. Rajput, S. Wibowo, C. Hao, M. Majmudar
2019 arXiv   pre-print
Following that, deep learning was used to train a deep neural network based classifier to detect arrhythmias.  ...  In this paper, 1-D time series data is converted into multi-dimensional representation in the form of multichannel 2-D images.  ...  This paper proposes an enhanced deep learning technique to detect arrhythmias in ECG.  ... 
arXiv:1904.00138v4 fatcat:tqz3z5r6tfdbzcpoaown4rfvpu

Depth Analysis of Single View Image Objects based on Object Detection and Focus Measure

Jyoti B. Kulkarni, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
2019 International Journal of Advanced Trends in Computer Science and Engineering  
In addition to that, the entropies of different objects computed as another evaluation metrics. Deep Learning used here for object detection from image and the depth map generated.  ...  In this paper, indoor images with different objects have considered and the focus measures of various objects in the images have calculated using Discrete Wavelet Transform (DWT) by considering it as one  ...  The object detection from the image has done by Deep Learning. [ 5 ] 5 . In Discrete Wavelet Transform, the image splits in 4 sub images. It is shown in Figurel (a).  ... 
doi:10.30534/ijatcse/2019/112852019 fatcat:iejpbfnwv5gmtk3c27l6irqwpu

Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection [article]

Ahmed Rasheed, Muhammad Shahzad Younis, Junaid Qadir, Muhammad Bilal
2021 arXiv   pre-print
Deep learning is widely used for the detection of cancerous masses in the images obtained via mammography.  ...  Our proposed system aids the radiologist in the screening phase of cancer detection by using a combination of segmentation and wavelet transforms as pre-processing augmentation that leads to transfer learning  ...  The success of AlexNet ushered in the era of deep learning and CNNs.• VGGNet: Simonyan and Zisserman in 2014 introduced a 19-layer deeper CNN achieving top results in ImageNet ILSVRC [7].  ... 
arXiv:2103.03602v1 fatcat:2ha2wn2v5ncopj4gdba5sjkmzy

Soft Autoencoder and Its Wavelet Adaptation Interpretation [article]

Fenglei Fan, Mengzhou Li, Yueyang Teng, Ge Wang
2021 arXiv   pre-print
As a successful unsupervised model in deep learning, the autoencoder embraces a wide spectrum of applications, yet it suffers from the model opaqueness as well.  ...  Recently, deep learning becomes the main focus of machine learning research and has greatly impacted many important fields. However, deep learning is criticized for lack of interpretability.  ...  In the era of big data, it is hypothesized that the most comprehensive information is contained in big data, and the best tool to dig them out is deep learning.  ... 
arXiv:1812.11675v4 fatcat:6qc46dhblbhkbcqsmdf6gmywg4

A Journey from basic Image Features to Lofty Human Intelligence in Content-based Image Retrieval: Motivation, Applications and Future Trends

2020 International journal of recent technology and engineering  
This paper presents a detailed study about the various basic techniques with an emphasis on different intelligent techniques like, the usage of machine learning, deep learning, relevance feedback, etc.  ...  Due to a remarkable increase in the complexity of the multimedia content, there is a cumulative enhancement of digital images both online and offline.  ...  Now, in this era, the focus of the researcher section has been shifted from machine learning to deep learning.  ... 
doi:10.35940/ijrte.b4011.079220 fatcat:aedu4uzoxrhafhab46ordfxm2m

Deep Learning Based Recurrent Neural Networks to Enhance the Performance of Wind Energy Forecasting: A Review

Senthil Kumar Paramasivan
2021 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
In the modern era, deep learning is a powerful technique in the field of wind energy forecasting.  ...  The overall review shows that the deep learning based RNN improves the performance of wind energy forecasting compared to the conventional techniques.  ...  INTRODUCTION In the modern era, the wind energy is attracted by many companies for power generation.  ... 
doi:10.18280/ria.350101 fatcat:kngcr6knszchnhjebmdhnurs2y

Image Style Transfer: from Artistic to Photorealistic [article]

Chenggui Sun, Li Bin Song
2022 arXiv   pre-print
The rapid advancement of deep learning has significantly boomed the development of photorealistic style transfer.  ...  However, our focus is on VGG-based techniques, whitening and coloring transform (WCTs) based techniques, the combination of deep learning with traditional image processing techniques.  ...  the booming of the deep learning era.  ... 
arXiv:2203.06328v1 fatcat:i3krcc2ux5hndf4mjxzl2gp3zi

A Deep-Learning-Based Bearing Fault Diagnosis Using Defect Signature Wavelet Image Visualization

Bach Phi Duong, Jae Young Kim, Inkyu Jeong, Kichang Im, Cheol Hong Kim, Jong Myon Kim
2020 Applied Sciences  
Using the resultant DSWI, the deep convolution neural network (DCNN) architecture is designed to identify the fault in the bearing.  ...  A novel strategy is propounded for the deployment of the continuous wavelet transform with damage frequency band information to generate the defect signature wavelet image (DSWI), which describes the acoustic  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app10248800 fatcat:upm77awlvrbkhfwvsbj4y2wyve

A Methodology for Exploring Deep Convolutional Features in Relation to Hand-Crafted Features with an Application to Music Audio Modeling [article]

Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier, Sayan Mukherjee, Vahid Tarokh
2021 arXiv   pre-print
Understanding the features learned by deep models is important from a model trust perspective, especially as deep systems are deployed in the real world.  ...  In this work, we instead take the perspective of relating deep features to well-studied, hand-crafted features that are meaningful for the application of interest.  ...  era.  ... 
arXiv:2106.00110v2 fatcat:q4ibl2peavgvfldua7e2sie4t4

Constructing a Reliable Health Indicator for Bearings Using Convolutional Autoencoder and Continuous Wavelet Transform

Mohammadreza Kaji, Jamshid Parvizian, Hans Wernher van de Venn
2020 Applied Sciences  
In general, predicting the RUL of a component includes constructing a health indicator () to infer the current condition of the component, and modelling the degradation process in order to estimate the  ...  For this purpose, the continuous wavelet transform (CWT) technique was used to convert the raw acquired vibrational signals into a two-dimensional image; then, the CAE model was trained by the healthy  ...  Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2020, 10, 8948  ... 
doi:10.3390/app10248948 fatcat:kgl23mmyf5gvxdxs3xtaiulziq

Boundary Preserved Salient Object Detection Using Guided Filter Based Hybridization Approach of Transformation and Spatial Domain Analysis

Bhagyashree V. Lad, Mohammad Farukh Hashmi, Avinash G. Keskar
2022 IEEE Access  
In this paper, a unique approach is proposed based on the global and local saliency detection using wavelet transform and hybridizing it with learning-based saliency detection using a guided filter.  ...  The paper discusses the novel technique for hybridizing wavelet-based and learning-based saliency maps using a guided filter-based attention map generation.  ...  In the era of deep learning-based methods, the employment of handcrafted feature-based algorithms and conventional computer vision techniques to solve SOD tasks is still highly significant [12] , [13  ... 
doi:10.1109/access.2022.3185409 fatcat:w7ufaautcjfojj4bau62opof5m

Knowledge extraction based on wavelets and DNN for classification of physiological signals: Arousals case

Edwar Macias Toro, Antoni Morell, Javier Serrano, Jose Lopez Vicario
2018 2018 Computing in Cardiology Conference (CinC)  
In this way, by segmenting the signals and decomposing them into variable frequency bands, thanks to the application of discrete wavelet transform (DWT), it is possible to characterize the contributions  ...  In this detection, the triggers can be present in any of the PS or can occur from their combinations.  ...  Acknowledgements This work is supported by the Spanish Government under Project TEC2017-84321-C4-4-R co-funded with European Union ERDF funds and also by the Catalan Government under Project 2017 SGR 1670  ... 
doi:10.22489/cinc.2018.230 dblp:conf/cinc/ToroM0V18 fatcat:h77kgjh7f5chtgq5d22eazhaby

End-to-End Training for Compound Expression Recognition

Hongfei Li, Qing Li
2020 Sensors  
learning for the recognition of compound expressions in the wild.  ...  We are mainly devoted to digging the appearance and geometric information based on deep learning models.  ...  of deep learning technology in various fields.  ... 
doi:10.3390/s20174727 pmid:32825666 pmcid:PMC7506941 fatcat:d6lrblpcp5hgnpyy26kcpr2l3m
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