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Comparative Survey of Signal Processing and Artificial Intelligence Based Channel Equalization Techniques and Technologies
2019
International Journal of Emerging Trends in Engineering Research
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It was found that gaps such as complexity and convergence time are potential areas for extending the performance and limits of existing channel equalizers. ...
The authors begin with the theory behind channel equalization followed by techniques, and the technological realizations for achieving the proper filter in response to variations of the channel. ...
Acknowledgment De La Salle University is acknowledged for supporting this work. ...
doi:10.30534/ijeter/2019/14792019
fatcat:rz2vabommrhdrgw47zpino5vou
View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
[article]
2019
arXiv
pre-print
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The source code is available at https://github.com/microsoft/View-Adaptive-Neural-Networks-for-Skeleton-based-Human-Action-Recognition. ...
We design two view adaptive neural networks, i.e., VA-RNN based on RNN, and VA-CNN based on CNN. ...
We have designed view adaptation models based on the recurrent neural network and the convolutional neural network respectively. ...
arXiv:1804.07453v3
fatcat:i22jzaufpbfupdki25tjemy4ca
Video Compression by Neural Networks
[chapter]
Intelligent Multimedia Processing with Soft Computing
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The new approach is based on a proper quad-tree segmentation of video frames and is capable to yield a considerable improvement with respect to existing standards in high quality video compression. ...
Standardization issues are briefly discussed and most recent neural compression techniques reviewed. In addition, a particularly effective novel neural paradigm is introduced and described. ...
Quad-tree segmentation and neural compression The following sections describe in detail two waveform video compression algorithms, based on the use of feedforward and locally recurrent neural networks. ...
doi:10.1007/3-540-32367-8_10
fatcat:opfmbhjjcjhxpmjq3c5cvp7ko4
Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs
2012
2012 IEEE Congress on Evolutionary Computation
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This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm. ...
using Recurrent Neural Networks 448, Kazuaki Masuda, Bunpei Fukui and Kenzo Kurihara, A Weighting Approach for Autoassociative Memories to Improve Accuracy in Memorization 625, Florian Jug, Matthew Cook ...
with a Feature Layer and a Nonlinear Readout 730, Oliver Obst and Martin Riedmiller, Taming the Reservoir Feedforward Training for Recurrent Neural Networks Tuesday, IJCNN, TuN 3-3, 13:30-14:30, Reinforcement ...
doi:10.1109/cec.2012.6256590
dblp:conf/cec/RotaruB12
fatcat:4ly3nrktw5habc6lf5err7d5py
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications
[article]
2016
arXiv
pre-print
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Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. ...
We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. ...
Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks (DBLSTM-RNN) are used in [107] . ...
arXiv:1606.03237v1
fatcat:t55kncgy6fgsvgi42pdgleu43m
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications
2016
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. ...
We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. ...
Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks (DBLSTM-RNN) are used in [107] . ...
doi:10.1109/tpami.2016.2515606
pmid:26761193
pmcid:PMC7426891
fatcat:ezwkw2bmhbdtlffz3uz3m3hoiy
Multimedia Internet of Things: A Comprehensive Survey
2020
IEEE Access
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Delaysensitive and bandwidth-hungry multimedia applications over constrained IoT networks require revision of IoT architecture for M-IoT. ...
, Fog/Edge computing and Software-Defined-Networks (SDNs). ...
The authors employed a Recurrent Neural Network (RNN) based Long Short-Term Memory (LSTM) unit on decoding fused data into multi-events labels. ...
doi:10.1109/access.2020.2964280
fatcat:ilihkpik65bdvblyal6rp7tb2y
2020 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 67
2020
IEEE Transactions on Circuits and Systems - II - Express Briefs
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., A Novel Dynamic Detection for Flash Memory; 600-604 Issakov, V., see Aguilar, E., TCSII May 2020 906-910 Iu, H.H., see Lai, Q., 1129-1133 Iu, H.H., see Xu, G., TCSII Dec. 2020 3452-3456 Iu, H.H.C ...
Eshraghian, J.K., TCSII May 2020 956-960 Iu, H.H.C., see Yu, D., 1334-1338 Iu, H.H.C., see Wang, L., TCSII Oct. 2020 2084-2088 J Jabavathi, J.D., and Sait, H., Design of a Single Chip PWM Driver Circuit for ...
Projection Recurrent Neural Network Model: A New Strategy to Solve Maximum Flow Problem. ...
doi:10.1109/tcsii.2020.3047305
fatcat:ifjzekeyczfrbp5b7wrzandm7e
Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces
[article]
2018
arXiv
pre-print
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The team would like to thank Metapraxis for supporting this project and lending us one of the tablets for the experiments. ...
The team would also like to thank the DeVisu laboratory for lending us the Tobii eyetracking glasses. The team would like to thank the TCTS laboratory for the WiFi hotspots. ...
For training the model, the system has implemented several algorithms with Weka, such as neural networks, decision trees, nearest neighbor algorithm, AdaBoost and support vector machines. ...
arXiv:1801.06349v1
fatcat:qauytivdq5axxis2xlknp3r2ne
Text Detection and Recognition in the Wild: A Review
[article]
2020
arXiv
pre-print
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Detection and recognition of text in natural images are two main problems in the field of computer vision that have a wide variety of applications in analysis of sports videos, autonomous driving, industrial ...
Second, identifying several existing challenges for detecting or recognizing text in the wild images, namely, in-plane-rotation, multi-oriented and multi-resolution text, perspective distortion, illumination ...
, ON Canada, for supporting this research work. ...
arXiv:2006.04305v2
fatcat:paccfprli5arbj4ggfx5z3hrve
A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster
2018
Cell
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Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. ...
enables brain-spanning mapping of circuits at synaptic resolution d All mushroom body (MB) calyx inputs were mapped, revealing a new cell type, MB-CP2 d Previously unidentified synaptic partners form recurrent ...
/DMG/
Signal-to-noise ratio quantification
This paper
https://github.com/bocklab/temca2data/tree/
master/SNR
Neuron skeleton analysis code
This paper
https://github.com/bocklab/temca2data/tree ...
doi:10.1016/j.cell.2018.06.019
pmid:30033368
pmcid:PMC6063995
fatcat:me3wn3utfrbuhi6byynila624a
Final Program
2020
2020 International Conference on Unmanned Aircraft Systems (ICUAS)
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We thank all of them for their extremely valuable contributions and dedication. Dr. ...
Athens is a magnificent location for such an international event like the 2020 ICUAS. ...
algorithm, with a k-d tree-based obstacle avoidance strategy and three-step optimization. ...
doi:10.1109/icuas48674.2020.9214039
fatcat:7jr6chhfija47kgtwoxqmfmmoe
2020 Index IEEE Transactions on Instrumentation and Measurement Vol. 69
2020
IEEE Transactions on Instrumentation and Measurement
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Converter Using All-Digital Nested Delay-Locked Loops With 50-ps Resolution and High Throughput for LiDAR TIM Nov. 2020 9262-9271 Helsen, J., see Huchel, L., TIM July 2020 4145-4153 Hemavathi, N., ...
of Rounds; TIM June 2020 3739-3749 Hendeby, G., see Kasebzadeh, P., TIM Aug. 2020 5862-5874 Heng, Y., see Xue, M., TIM June 2020 3812-3817 Henry, M.P., The Prism: Recursive FIR Signal Processing for ...
Neural Networks. ...
doi:10.1109/tim.2020.3042348
fatcat:a5f4fsqs45fbbetre6zwsg3dly
Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art
[article]
2021
arXiv
pre-print
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2019 pre-print arXiv:1704.05519v2 fatcat:vg2fezsgyzgptbpbvnwcpw24qyOther Versions
While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. ...
relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for ...
They use this mid-level representation as input to a recurrent neural network (RNN) which outputs the control command. Similarly, Wang et al. ...
arXiv:1704.05519v3
fatcat:xiintiarqjbfldheeg2hsydyra
Representation, Analysis, and Recognition of 3D Humans
2018
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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For many years, 2D still images and videos have been used as the only sources to investigate methods for detecting, representing and analyzing human body and face [176] . ...
Methods based on 2D images and videos are the most widespread, but there is a recent trend that successfully extends the study to 3D human data as acquired by a new generation of 3D acquisition devices ...
Deep Convolutional Neural Networks (CNNs) have brought about breakthroughs in processing images, videos, speech and audio, whereas Recurrent NN have shown light on sequential data such as text and speech ...
doi:10.1145/3182179
fatcat:ds55t4md2na2tibtyg4llerf3q
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