SOMprocessor: A high throughput FPGA-based architecture for implementing Self-Organizing Maps and its application to video processing

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Self-organized formation of topographically correct feature maps

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Essentials of the self-organizing map

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Clustering high-dimensional data

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Free viewpoint action recognition using motion history volumes

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Topology preservation in self-organizing maps

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FPGA Implementations of Neural Networks

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Performance comparison of FPGA, GPU and CPU in image processing

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Recent survey on crowd density estimation and counting for visual surveillance

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Web page clustering using a self-organizing map of user navigation patterns

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A 75-µW, 16-Channel Neural Spike-Sorting Processor With Unsupervised Clustering

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Embedded Streaming Deep Neural Networks Accelerator With Applications

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2015 IEEE 39th Annual Computer Software and Applications Conference

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Topology Preservation in Self-Organizing Maps

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Unsupervised speaker recognition based on competition between self-organizing maps

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A massively parallel architecture for self-organizing feature maps

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IP core implementation of a self-organizing neural network

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Novel FPGA Implementation of Hand Sign Recognition System With SOM–Hebb Classifier

Hikawa, H., & Kaida, K. (2015) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2014.2335831 · Cited by 59 · see citing works

2010 Prognostics and System Health Management Conference

(2010) · doi:10.1109/phm15953.2010 · Cited by 58 · see citing works

FPGA implementation of self organizing map with digital phase locked loops

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On the A.S. Convergence of the Kohonen Algorithm with a General Neighborhood Function

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A hardware design of a massive-parallel, modular NN-based vector quantizer for real-time video coding

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Parallel Programmable Asynchronous Neighborhood Mechanism for Kohonen SOM Implemented in CMOS Technology

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Improved Learning Performance of Hardware Self-Organizing Map Using a Novel Neighborhood Function

Hikawa, H., & Maeda, Y. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2398932 · Cited by 42 · see citing works

2008 International Conference on Field Programmable Logic and Applications

(2008) · doi:10.1109/fpl13823.2008 · Cited by 41 · see citing works

Fault Detection, Diagnosis and Prediction in Electrical Valves Using Self-Organizing Maps

Gonçalves, L. F., Bosa, J. L., Balen, T. R., Lubaszewski, M. S., Schneider, E. L., & Henriques, R. V. B. (2011) · Journal of Electronic Testing · doi:10.1007/s10836-011-5220-0 · Cited by 40 · see citing works

2014 19th International Conference on Digital Signal Processing

(2014) · doi:10.1109/dsp33716.2014 · Cited by 40 · see citing works

A reconfigurable neuroprocessor for self-organizing feature maps

Lachmair, J., Merényi, E., Porrmann, M., & Rückert, U. (2013) · Neurocomputing · doi:10.1016/j.neucom.2012.11.045 · Cited by 39 · see citing works

Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware

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Analog Programmable Distance Calculation Circuit for Winner Takes All Neural Network Realized in the CMOS Technology

Talaśka, T., Kolasa, M., Dlugosz, R. T., & Pedrycz, W. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2434847 · Cited by 37 · see citing works

2007 14th International Conference on Mixed Design of Integrated Circuits and Systems

(2007) · doi:10.1109/mixdes12653.2007 · Cited by 33 · see citing works

A novel hardware-oriented Kohonen SOM image compression algorithm and its FPGA implementation

Kurdthongmee, W. (2008) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2008.04.007 · Cited by 32 · see citing works

A parallel adaptive segmentation method based on SOM and GPU with application to MRI image processing

De, A., Zhang, Y., & Guo, C. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.10.129 · Cited by 32 · see citing works

AW-SOM, an Algorithm for High-Speed Learning in Hardware Self-Organizing Maps

Cardarilli, G. C., Nunzio, L. D., Fazzolari, R., Re, M., & Spanò, S. (2019) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2019.2909117 · Cited by 32 · see citing works

2013 International Symposium on Intelligent Signal Processing and Communication Systems

(2013) · doi:10.1109/ispacs30637.2013 · Cited by 32 · see citing works

Fast Neuromimetic Object Recognition Using FPGA Outperforms GPU Implementations

Orchard, G., Martin, J. G., Vogelstein, R. J., & Etienne‐Cummings, R. (2013) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2253563 · Cited by 31 · see citing works

Digital Hardware Architectures of Kohonen's Self Organizing Feature Maps with Exponential Neighboring Function

Peña, J., Vanegas, M., & Valencia, A. H. (2006) · doi:10.1109/reconf.2006.307761 · Cited by 29 · see citing works

Teaching emotion expressions to a human companion robot using deep neural architectures

Churamani, N., Kerzel, M., Strahl, E., Barros, P. V. A., & Wermter, S. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7965911 · Cited by 29 · see citing works

Implementation and applications of tri-state self-organizing maps on FPGA

Appiah, K., Hunter, A., Dickinson, P., & Meng, H. (2012) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2012.2197077 · Cited by 28 · see citing works

Epileptic Seizure Prediction from EEG Signals Using Unsupervised Learning and a Polling-Based Decision Process

Kitano, L. A. S., de Sousa, M. A. D. A., dos Santos, S. D., Pires, R., Thomé-Souza, S., & Campo, A. B. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01421-6_12 · Cited by 28 · see citing works

High Throughput Systolic SOM IP Core for Fpgas

Manolakos, E. S., & Logaras, E. (2007) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2007.366172 · Cited by 27 · see citing works

Self-organizing map hardware accelerator system and its application to realtime image enlargement

Tamukoh, H., Aso, T., Horio, K., & Yamakawa, T. (2005) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2004.1381073 · Cited by 27 · see citing works

On the AER convolution processors for FPGA

Linares-Barranco, A., Paz-Vicente, R., Gómez-Rodríguez, F., Jimenez, A., Rivas, M., Jiménez, G., & Civit, A. (2010) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2010.5537577 · Cited by 26 · see citing works

Monitoring of complex industrial processes based on self-organizing maps and watershed transformations

Frey, C. W. (2012) · IEEE International Conference on Industrial Technology (ICIT) · doi:10.1109/icit.2012.6210077 · Cited by 25 · see citing works

A binary Self-Organizing Map and its FPGA implementation

Appiah, K., Hunter, A., Meng, H., Yue, S., Hobden, M., Priestley, N., Hobden, P., & Pettit, C. (2009) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2009.5179001 · Cited by 25 · see citing works

Artificial Intelligence in the Path Planning Optimization of Mobile Agent Navigation

Brassai, S. T., Iantovics, L. B., & Calin, E. (2012) · Procedia Economics and Finance · doi:10.1016/s2212-5671(12)00147-5 · Cited by 24 · see citing works

Predictive self-organizing map for vector quantization of migratory signals and its application to mobile communications

Hirose, A., & Nagashima, T. (2003) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2003.820834 · Cited by 24 · see citing works

A scalable and adaptable hardware NoC-based self organizing map

Abadi, M., Jovanović, S., Khalifa, K. B., Weber, S., & Bedoui, M. H. (2017) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2017.12.007 · Cited by 24 · see citing works

The International Computer Science and Engineering Conference

(2021) · International Computer Science and Engineering Conference · doi:10.1109/icsec53205.2021.9684618 · Cited by 24 · see citing works

A Spatio-Temporal Architecture for Context Aware Sensing

Thiemjarus, S., Lo, B. P. L., & Yang, G. (2006) · International Workshop on Wearable and Implantable Body Sensor Networks (BSN) · doi:10.1109/bsn.2006.5 · Cited by 23 · see citing works

Implementation of Self-Organizing Feature Maps in Reconfigurable Hardware

Porrmann, M., Witkowski, U., & Rückert, U. (2006) · Springer eBooks · doi:10.1007/0-387-28487-7_9 · Cited by 22 · see citing works

An FPGA distributed implementation model for embedded SOM with on-line learning

de Sousa, M. A. D. A., & Del-Moral-Hernandez, E. (2017) · doi:10.1109/ijcnn.2017.7966351 · Cited by 21 · see citing works

A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression

Huang, Z., Zhang, X., Chen, L., Zhu, Y., An, F., Wang, H., & Feng, S. (2017) · Applied Sciences · doi:10.3390/app7111106 · Cited by 20 · see citing works

A novel robust approach for handling illumination changes in video segmentation

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Comparison of three FPGA architectures for embedded multidimensional categorization through Kohonen's self-organizing maps

de Abreu de Sousa, M. A., & Del-Moral-Hernandez, E. (2017) · 2017 IEEE International Symposium on Circuits and Systems (ISCAS) · doi:10.1109/iscas.2017.8050799 · Cited by 18 · see citing works

Hierarchies of Self-Organizing Maps for action recognition

Buonamente, M., Dindo, H., & Johnsson, M. (2016) · Cognitive Systems Research · doi:10.1016/j.cogsys.2015.12.009 · Cited by 17 · see citing works

From CPU to FPGA — Acceleration of self-organizing maps for data mining

Lachmair, J., Mieth, T., Griessl, R., Hagemeyer, J., & Porrmann, M. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7966400 · Cited by 17 · see citing works

An integrated incremental self-organizing map and hierarchical neural network approach for cognitive radio learning

Cai, Q., Chen, S., Li, X., Hu, N., He, H., Yao, Y., & Mitola, J. (2010) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2010.5596337 · Cited by 15 · see citing works

An FPGA-Based Real-Time Maximum Likelihood 3D Position Estimation for a Continuous Crystal PET Detector

Wang, Y., Xiao, Y., Cheng, X., Li, D., & Wang, L. (2016) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2015.2506739 · Cited by 15 · see citing works

Object detection in video sequences by a temporal modular self-adaptive SOM

Ramírez-Alonso, G. M. D. J., & Chacon-Murguia, M. I. (2015) · Neural Computing and Applications · doi:10.1007/s00521-015-1859-2 · Cited by 13 · see citing works

A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network

Khalifa, K. B., Blaiech, A. G., & Bedoui, M. H. (2019) · Computational Intelligence and Neuroscience · doi:10.1155/2019/8212867 · Cited by 13 · see citing works

A hand shape instruction recognition and learning system using growing SOM with asymmetric neighborhood function

Kuremoto, T., Otani, T., Obayashi, M., Kobayashi, K., & Mabu, S. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.10.108 · Cited by 13 · see citing works

A fast Kohonen net implementation for spert-II

Asanović, K. (1997) · Lecture notes in computer science · doi:10.1007/bfb0032538 · Cited by 12 · see citing works

Performance analysis of arc welding parameters using self organizing maps and probability density distributions

Kumar, V., Albert, S. K., Chandrasekhar, N., Jayapandian, J., & Venkatesan, M. V. (2016) · IEEE International Conference on Control, Measurement and Instrumentation · doi:10.1109/cmi.2016.7413738 · Cited by 12 · see citing works

A Vector-Quantization Compression Circuit With On-Chip Learning Ability for High-Speed Image Sensor

Huang, Z., Zhang, X., Chen, L., Zhu, Y., An, F., Wang, H., & Feng, S. (2017) · IEEE Access · doi:10.1109/access.2017.2762399 · Cited by 12 · see citing works

TEMPORAL BAG-OF-WORDS - A Generative Model for Visual Place Recognition using Temporal Integration

Guillaume, H., Dubois, M., Frenoux, E., & Tarroux, P. (2011) · International Conference on Computer Vision Theory and Applications · doi:10.5220/0003353202860295 · Cited by 11 · see citing works

An FPGA-based SOM circuit architecture for online learning of 64-QAM data streams

de Sousa, M. A. D. A., Pires, R., Perseghini, S. D. D. S., & Del-Moral-Hernandez, E. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489518 · Cited by 11 · see citing works

Toward a Sparse Self-Organizing Map for Neuromorphic Architectures

Rodriguez, L., Miramond, B., & Granado, B. (2015) · ACM Journal on Emerging Technologies in Computing Systems · doi:10.1145/2638559 · Cited by 10 · see citing works

A hardware configurable self-organizing map for real-time color quantization

Abadi, M., Jovanović, S., Khalifa, K. B., Weber, S., & Bedoui, M. H. (2016) · IEEE International Conference on Electronics, Circuits and Systems (ICECS) · doi:10.1109/icecs.2016.7841201 · Cited by 10 · see citing works

Classification of epileptiform events in EEG signals using neural classifier based on SOM

Azevedo, C. R., Boos, C. F., & de Azevedo, F. M. (2015) · International Conference on Electrical Engineering and Information Communication Technology · doi:10.1109/iceeict.2015.7307340 · Cited by 9 · see citing works

Self-Organizing Map With Time-Varying Structure to Plan and Control Artificial Locomotion

Araujo, A. F. R., & Santana, O. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2014.2345662 · Cited by 9 · see citing works

Supervised learning of DPLL based winner-take-all neural network

Azuma, M., & Hikawa, H. (2014) · doi:10.1109/ices.2014.7008730 · Cited by 9 · see citing works

Application of the Wavelet-SOFM Network in Roll Bearing Defect Diagnosis

He, W., & Zhou, X. (2009) · WRI Global Congress on Intelligent Systems · doi:10.1109/gcis.2009.132 · Cited by 9 · see citing works

Panoramic background modeling for PTZ cameras with competitive learning neural networks

Thurnhofer‐Hemsi, K., López‐Rubio, E., Domínguez, E., Luque‐Baena, R. M., & Molina‐Cabello, M. A. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7965881 · Cited by 9 · see citing works

Constructivist ambient intelligent agent for smart environments

Najjar, A., & Reignier, P. (2013) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2013.6529515 · Cited by 8 · see citing works

2006 IEEE International Conference on Reconfigurable Computing and FPGA's

(2006) · International Conference on ReConFigurable Computing and FPGAs (ReConFig) · doi:10.1109/reconf.2006.307740 · Cited by 8 · see citing works

Efficient methods of initializing neuron weights in self-organizing networks implemented in hardware

Kolasa, M., Dlugosz, R. T., Talaśka, T., & Pedrycz, W. (2017) · Applied Mathematics and Computation · doi:10.1016/j.amc.2017.01.043 · Cited by 8 · see citing works

Self-organization map of spiking neurons evaluation in phoneme classification

Behi, T., Arous, N., & Ellouze, N. (2012) · International Conference on Sciences of Electronics, Technologies of Information and Telecommunications · doi:10.1109/setit.2012.6481999 · Cited by 7 · see citing works

A low latency minimum distance searching unit of the SOM based hardware quantizer

Kurdthongmee, W. (2015) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2015.01.009 · Cited by 7 · see citing works

Self-Organizing Map Neural Network-Based Depth-of-Interaction Determination for Continuous Crystal PET Detectors

Wang, Y., Wang, L., Li, D., Cheng, X., & Xiao, Y. (2015) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2015.2421290 · Cited by 7 · see citing works

OFDM symbol identification by an unsupervised learning system under dynamically changing channel effects

de Sousa, M. A. D. A., Pires, R., & Del-Moral-Hernandez, E. (2017) · Neural Computing and Applications · doi:10.1007/s00521-017-2957-0 · Cited by 7 · see citing works

Kohonen winner takes all neural network realized on microcontrollers with AVR and ARM cores

Przedwojski, P., Dalecki, J., Talaśka, T., & Dlugosz, R. T. (2010) · International Conference Mixed Design of Integrated Circuits and Systems · Cited by 6 · see citing works

Event definition for stability preservation in bio-inspired cognitive crowd monitoring

Chiappino, S., Morerio, P., Marcenaro, L., & Regazzoni, C. S. (2013) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1109/icdsp.2013.6622802 · Cited by 6 · see citing works

Remote fault diagnostic model for tribological systems in marine diesel engine with two-level self-organizing map network

Xu, X., Xinping, Y., Jiangbin, Z., Sheng, C., Chengqing, Y., & Dongzhi, M. (2014) · Prognostics and System Health Management Conference · doi:10.1109/phm.2014.6988175 · Cited by 6 · see citing works

Binary object recognition system on FPGA with bSOM

Appiah, K., Hunter, A., Dickinson, P., & Meng, H. (2010) · IEEE International SOC Conference (SOCC) · doi:10.1109/socc.2010.5784755 · Cited by 6 · see citing works

Detecting driving drowsiness using EEG, EOG and driving quality signals

Noori, S. M. R., & Mikaeili, M. (2015) · Iranian Conference on Biomedical Engineering · doi:10.1109/icbme.2015.7404144 · Cited by 6 · see citing works

2014 IEEE International Conference on Evolvable Systems

(2014) · doi:10.1109/ices33885.2014 · Cited by 6 · see citing works

Efficient event-driven approach using synchrony processing for hardware spiking neural networks

Seguin-Godin, G., Mailhot, F., & Rouat, J. (2015) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2015.7169242 · Cited by 5 · see citing works

Electronic nose for on-line quality evaluation of black tea using incremental SOM techniques

Ghosh, S., Bhattacharyya, N., Tudu, B., & Bandyopadhyay, R. (2015) · International Symposium on Physics and Technology of Sensors · doi:10.1109/ispts.2015.7220128 · Cited by 5 · see citing works

Utilization of a rational-based representation to improve the image quality of a hardware-based K-SOM quantizer

Kurdthongmee, W. (2011) · Journal of Real-Time Image Processing · doi:10.1007/s11554-011-0199-4 · Cited by 5 · see citing works

Winner-take-all neural network with digital frequency-locked loop

Hikawa, H. (2015) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2015.7169197 · Cited by 4 · see citing works

Color-space image compression with hardware Self-organizing map

Terahara, N., Oba, Y., & Hikawa, H. (2013) · International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) · doi:10.1109/ispacs.2013.6704514 · Cited by 4 · see citing works

23rd IEEE International SOC Conference

(2010) · doi:10.1109/socc16611.2010 · Cited by 4 · see citing works

An SOM-Based Motion Trajectory Recognition Algorithm and Its Application in Monitoring Therapeutic Exercises

Su, M. (2015) · IEEE Annual Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2015.204 · Cited by 3 · see citing works

2012 Western New York Image Processing Workshop

(2012) · doi:10.1109/wnyipw31050.2012 · Cited by 3 · see citing works

A two-stage SOM for noise reduction in SOM map

Apinantanakon, W., & Sunat, K. (2014) · International Computer Science and Engineering Conference · doi:10.1109/icsec.2014.6978194 · Cited by 2 · see citing works

A serial distance calculation circuit for the application in artificial neural networks and pattern recognition

Kolasa, M., Talaśka, T., & Dlugosz, R. T. (2017) · International Conference Mixed Design of Integrated Circuits and Systems · doi:10.23919/mixdes.2017.8005263 · Cited by 2 · see citing works

A Hand Shape Instruction Recognition and Learning System Using Growing SOM with Asymmetric Neighborhood Function

Kuremoto, T., Otani, T., Obayashi, M., Kobayashi, K., & Mabu, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-09333-8_29 · Cited by 1 · see citing works

Unsupervised learning of video content using Self-Organizing Maps

Gaborski, R. S., & Wang, Y. (2011) · doi:10.1109/wnyipw.2011.6122882 · Cited by 1 · see citing works

Hybrid multi-mode machine learning-based fault diagnosis strategies with application to aircraft gas turbine engines

Shen, Y., & Khorasani, K. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.07.001 · Cited by 124 · see citing works

Embedded Intelligence on FPGA: Survey, Applications and Challenges

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A Survey of Hardware Self-Organizing Maps

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Hardware Self-Organizing Map Based on Digital Frequency-Locked Loop and Triangular Neighborhood Function

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Design and Implementation of Embedded Real-Time English Speech Recognition System Based on Big Data Analysis

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SESOMP: A Scalable and Energy-Efficient Self-Organizing Map Processor with Computing-In-Memory and Dead Neuron Pruning

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A cascade perceptron and Kohonen network approach to fault location in rural distribution feeders

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A highly scalable Self-organizing Map accelerator on FPGA and its performance evaluation

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A Data Sharing and Integration Technology for Heterogeneous Databases

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An Efficient Parallel CRC Computing Method for High Bandwidth Networks and FPGA Implementation

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Place-and-Route Analysis of FPGA Implementation of Nested Hardware Self-Organizing Map Architecture

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Nested Pipeline Hardware Self-Organizing Map for High Dimensional Vectors

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HLS-Based Large Scale Self-Organizing Feature Maps

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SESOMP: A Scalable and Energy-Efficient Self-Organizing Map Processor for IoT Devices

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A New Hardware Approach to Self-Organizing Maps

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Video Chunk Processor: Low-Latency Parallel Processing of 3 x 3-pixel Image Kernels

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Reconfigurable Electronic Platforms: A Top-Down Approach to Learn about Design and Integration of Electronic Systems

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Previsão de surtos epiléticos usando Mapas Auto Organizáveis executados diretamente em hardware

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Learning Rule Optimization and Comparative Evaluation of Accelerated Self-Organizing Maps for Industrial Applications

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A Matching Method of Heterogeneous Database based on SOM and BP Neural Network

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Design of low-power gesture recognition system and self-organizing map processors

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Hardware Self-Organizing Map With Dithered Step Neighborhood Function

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Interpretable inverse iteration mean shift networks for clustering tasks

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An Area-Efficient and Low-Error FPGA-Based Sigmoid Function Approximation

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Edge-Cell Graph Encoding and Fixed-Point Arithmetic for FPGA Growing Neural Gas

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A Systolic Hardware Architecture of Self-Organizing Map

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A full-parallel implementation of Self-Organizing Maps on hardware

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A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network

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