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SN
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RESEARCH
DOMAIN
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RESOURCE
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MOST CITED BY PAPERS 1
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MOST CITED BY PAPERS 2
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1
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IMAGE
PROCESSING
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IEEE
XPLORE
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S. Ren, K. He, R. Girshick and J. Sun, "Faster R-CNN:
Towards Real-Time Object Detection with Region Proposal Networks," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137-1149, 1 June 2017.
doi: 10.1109/TPAMI.2016.2577031
keywords: {Proposals;Object
detection;Convolutional codes;Feature extraction;Search
problems;Detectors;Training;Object detection;region proposal;convolutional
neural network},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7485869&isnumber=7919342
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S. J. Pan and Q. Yang, "A Survey on Transfer
Learning," in IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 10, pp. 1345-1359, Oct. 2010.
doi: 10.1109/TKDE.2009.191
keywords: {Machine learning;Training data;Data
mining;Knowledge transfer;Space technology;Knowledge engineering;Machine
learning algorithms;Labeling;Learning systems;Testing;Transfer
learning;survey;machine learning;data mining.},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5288526&isnumber=5550977
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2
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ARTIFICIAL
INTELLIGENCE
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IEEE
XPLORE
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L. -C. Chen, G. Papandreou, I. Kokkinos, K. Murphy and A. L.
Yuille, "DeepLab: Semantic Image Segmentation with Deep Convolutional
Nets, Atrous Convolution, and Fully Connected CRFs," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 4, pp. 834-848, 1 April 2018.
doi: 10.1109/TPAMI.2017.2699184
keywords: {Convolution;Image
segmentation;Semantics;Image resolution;Computational modeling;Neural
networks;Context;Convolutional neural networks;semantic segmentation;atrous
convolution;conditional random fields},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7913730&isnumber=8306529
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V. Badrinarayanan, A. Kendall and R. Cipolla, "SegNet: A
Deep Convolutional Encoder-Decoder Architecture for Image Segmentation,"
in IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 39, no. 12, pp. 2481-2495, 1 Dec. 2017.
doi: 10.1109/TPAMI.2016.2644615
keywords: {Decoding;Neural
networks;Training;Computer architecture;Image
segmentation;Semantics;Convolutional codes;Deep convolutional neural
networks;semantic pixel-wise segmentation;indoor scenes;road
scenes;encoder;decoder;pooling;upsampling},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7803544&isnumber=8094206
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3
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MACHINE
LEARNING
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IEEE
XPLORE
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S. Ren, K. He, R. Girshick and J. Sun, "Faster R-CNN:
Towards Real-Time Object Detection with Region Proposal Networks," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137-1149, 1 June 2017.
doi: 10.1109/TPAMI.2016.2577031
keywords: {Proposals;Object
detection;Convolutional codes;Feature extraction;Search
problems;Detectors;Training;Object detection;region proposal;convolutional
neural network},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7485869&isnumber=7919342
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S. J. Pan and Q. Yang, "A Survey on Transfer
Learning," in IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 10, pp. 1345-1359, Oct. 2010.
doi: 10.1109/TKDE.2009.191
keywords: {Machine learning;Training data;Data
mining;Knowledge transfer;Space technology;Knowledge engineering;Machine
learning algorithms;Labeling;Learning systems;Testing;Transfer
learning;survey;machine learning;data mining.},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5288526&isnumber=5550977
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4
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DEEP
LEARNING
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IEEE
XPLORE
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S. Ren, K. He, R. Girshick and J. Sun, "Faster R-CNN:
Towards Real-Time Object Detection with Region Proposal Networks," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137-1149, 1 June 2017.
doi: 10.1109/TPAMI.2016.2577031
keywords: {Proposals;Object
detection;Convolutional codes;Feature extraction;Search
problems;Detectors;Training;Object detection;region proposal;convolutional
neural network},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7485869&isnumber=7919342
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L. -C. Chen, G. Papandreou, I. Kokkinos, K. Murphy and A. L.
Yuille, "DeepLab: Semantic Image Segmentation with Deep Convolutional
Nets, Atrous Convolution, and Fully Connected CRFs," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 4, pp. 834-848, 1 April 2018.
doi: 10.1109/TPAMI.2017.2699184
keywords: {Convolution;Image
segmentation;Semantics;Image resolution;Computational modeling;Neural
networks;Context;Convolutional neural networks;semantic segmentation;atrous
convolution;conditional random fields},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7913730&isnumber=8306529
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5
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CLOUD
COMPUTING
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IEEE
XPLORE
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Y. Bengio, A. Courville and P. Vincent, "Representation
Learning: A Review and New Perspectives," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 8, pp. 1798-1828, Aug. 2013.
doi: 10.1109/TPAMI.2013.50
keywords: {Learning systems;Machine
learning;Abstracts;Feature extraction;Manifolds;Neural networks;Speech
recognition;Deep learning;representation learning;feature
learning;unsupervised learning;Boltzmann machine;autoencoder;neural nets},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6472238&isnumber=6541932
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J. G. Andrews et al., "What Will 5G Be?," in IEEE Journal on Selected Areas in Communications, vol. 32, no. 6, pp. 1065-1082, June 2014.
doi: 10.1109/JSAC.2014.2328098
keywords: {Special issues and sections;Macrocell
networks;Wireless communication;IEEE 802.11 Standards;Energy
efficiency;Bandwidth;Millimeter wave technology;MIMO;Mobile
communication;Cellular systems;energy efficiency;HetNets;massive
MIMO;millimeter wave;small cells},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6824752&isnumber=6862080
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6
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BIG
DATA
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IEEE
XPLORE
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S. J. Pan and Q. Yang, "A Survey on Transfer
Learning," in IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 10, pp. 1345-1359, Oct. 2010.
doi: 10.1109/TKDE.2009.191
keywords: {Machine learning;Training data;Data
mining;Knowledge transfer;Space technology;Knowledge engineering;Machine
learning algorithms;Labeling;Learning systems;Testing;Transfer
learning;survey;machine learning;data mining.},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5288526&isnumber=5550977
|
V. Badrinarayanan, A. Kendall and R. Cipolla, "SegNet: A Deep
Convolutional Encoder-Decoder Architecture for Image Segmentation," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 12, pp. 2481-2495, 1 Dec. 2017.
doi: 10.1109/TPAMI.2016.2644615
keywords: {Decoding;Neural networks;Training;Computer
architecture;Image segmentation;Semantics;Convolutional codes;Deep
convolutional neural networks;semantic pixel-wise segmentation;indoor
scenes;road scenes;encoder;decoder;pooling;upsampling},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7803544&isnumber=8094206
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7
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VLSI
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IEEE
XPLORE
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I. Tal and A. Vardy, "List Decoding of Polar Codes,"
in IEEE Transactions on Information Theory, vol. 61, no. 5, pp. 2213-2226, May 2015.
doi: 10.1109/TIT.2015.2410251
keywords: {Maximum likelihood
decoding;Arrays;Complexity theory;Parity check codes;Vectors;Bit error
rate;List decoding;polar codes;successive cancellation decoding;List
decoding;polar codes;successive cancellation decoding},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7055304&isnumber=7088688
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C. -C. Liu, S. -J. Chang, G. -Y. Huang and Y. -Z. Lin, "A
10-bit 50-MS/s SAR ADC With a Monotonic Capacitor Switching Procedure,"
in IEEE Journal of Solid-State Circuits, vol. 45, no. 4, pp. 731-740, April 2010.
doi: 10.1109/JSSC.2010.2042254
keywords: {Capacitors;CMOS
technology;Capacitance;Voltage;Power dissipation;Energy
consumption;Analog-digital conversion;Energy efficiency;Sampling methods;CMOS
process;Analog-to-digital converter;energy efficient;low power;successive
approximation register},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5437496&isnumber=5437471
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8
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IOT
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IEEE
XPLORE
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A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari and M.
Ayyash, "Internet of Things: A Survey on Enabling Technologies,
Protocols, and Applications," in IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347-2376, Fourthquarter 2015.
doi: 10.1109/COMST.2015.2444095
keywords: {Internet of things;Computer
architecture;Radiofrequency identification;Intelligent sensors;Mobile
communication;Internet of things;IoT;CoAP;MQTT;AMQP;XMPP;DDS;mDNS;IoT
Gateway;Internet of Things (IoT);CoAP;MQTT;AMQP;XMPP;DDS;mDNS;IoT gateway},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7123563&isnumber=7331734
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W. Shi, J. Cao, Q. Zhang, Y. Li and L. Xu, "Edge Computing:
Vision and Challenges," in IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646, Oct. 2016.
doi: 10.1109/JIOT.2016.2579198
keywords: {Cloud computing;Internet of
things;Bandwidth;Time factors;Mobile handsets;Data privacy;Smart homes;Edge
computing;Internet of Things (IoT);smart home and city},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7488250&isnumber=7563473
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9
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CYBER
SECURITY
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IEEE
XPLORE
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A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari and M.
Ayyash, "Internet of Things: A Survey on Enabling Technologies,
Protocols, and Applications," in IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347-2376, Fourthquarter 2015.
doi: 10.1109/COMST.2015.2444095
keywords: {Internet of things;Computer
architecture;Radiofrequency identification;Intelligent sensors;Mobile communication;Internet
of things;IoT;CoAP;MQTT;AMQP;XMPP;DDS;mDNS;IoT Gateway;Internet of Things
(IoT);CoAP;MQTT;AMQP;XMPP;DDS;mDNS;IoT gateway},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7123563&isnumber=7331734
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E. G. Larsson, O. Edfors, F. Tufvesson and T. L. Marzetta,
"Massive MIMO for next generation wireless systems," in IEEE Communications Magazine, vol. 52, no. 2, pp. 186-195, February 2014.
doi: 10.1109/MCOM.2014.6736761
keywords: {MIMO;Base stations;Antenna
arrays;Uplink;Fading;Downlink},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6736761&isnumber=6736727
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10
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BLOCKCHAIN
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IEEE
XPLORE
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K. Christidis and M. Devetsikiotis, "Blockchains and Smart
Contracts for the Internet of Things," in IEEE Access, vol. 4, pp. 2292-2303, 2016.
doi: 10.1109/ACCESS.2016.2566339
keywords: {Distributed processing;Internet of
things;Cryptography;Privacy;Blockchains;Automation;Peer-to-peer
computing;blockchain;distributed systems;Internet of
Things;Blockchain;distributed systems;internet of things},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7467408&isnumber=7419931
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W. Saad, M. Bennis and M. Chen, "A Vision of 6G Wireless
Systems: Applications, Trends, Technologies, and Open Research
Problems," in IEEE Network, vol. 34, no. 3, pp. 134-142, May/June 2020.
doi: 10.1109/MNET.001.1900287
keywords: {6G mobile communication;5G mobile
communication;Market research;Wireless communication;Sensors;Wireless sensor
networks},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8869705&isnumber=9105918
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11
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NOMA
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IEEE
XPLORE
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L. Dai, B. Wang, Y. Yuan, S. Han, I. Chih-lin and Z. Wang,
"Non-orthogonal multiple access for 5G: solutions, challenges,
opportunities, and future research trends," in IEEE Communications Magazine, vol. 53, no. 9, pp. 74-81, September 2015.
doi: 10.1109/MCOM.2015.7263349
keywords: {Multiplexing;Receivers;Silicon
carbide;Uplink;Multiaccess communication;Interference;5G mobile
communication},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7263349&isnumber=7263333
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Z. Ding, X. Lei, G. K. Karagiannidis, R. Schober, J. Yuan and V.
K. Bhargava, "A Survey on Non-Orthogonal Multiple Access for 5G
Networks: Research Challenges and Future Trends," in IEEE Journal on Selected Areas in Communications, vol. 35, no. 10, pp. 2181-2195, Oct. 2017.
doi: 10.1109/JSAC.2017.2725519
keywords: {NOMA;5G mobile communication;Quality
of service;Resource management;Millimeter wave communication;MIMO;Cognitive
radio;Non-orthogonal multiple access (NOMA);multi-carrier NOMA;MIMO;cooperative
NOMA;millimeter-wave networks},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7973146&isnumber=8038094
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12
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WIND
TURBINE MONITORING
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IEEE
XPLORE
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J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna and M.
Castilla, "Hierarchical Control of Droop-Controlled AC and DC
Microgrids—A General Approach Toward Standardization," in IEEE Transactions on Industrial Electronics, vol. 58, no. 1, pp. 158-172, Jan. 2011.
doi: 10.1109/TIE.2010.2066534
keywords: {Standardization;Control
systems;Energy resources;Energy storage;Dispatching;Impedance;Power system
restoration;Energy management;Power system management;Load flow;Distributed
generation (DG);distributed power systems;droop method;hierarchical
control;ISA-95;microgrid (MG);parallel operation;smart grid (SG)},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5546958&isnumber=5662271
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J. Rocabert, A. Luna, F. Blaabjerg and P. RodrÃguez,
"Control of Power Converters in AC Microgrids," in IEEE Transactions on Power Electronics, vol. 27, no. 11, pp. 4734-4749, Nov. 2012.
doi: 10.1109/TPEL.2012.2199334
keywords: {Voltage
control;Synchronization;Impedance;Frequency conversion;Generators;Reactive
power;Frequency control;Active and reactive power droop control;ancillary
services;distributed energy resources;distributed generation (DG);grid
converter control;grid synchronization;microgrids},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6200347&isnumber=6222041
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