*NOTE: These videos were recorded in Fall 2015 to update the Neural Nets portion of the class. MIT 6.034 Artificial Intelligence, Fall 2010 View the complete...
What are Convolutional Neural Networks and why are they important? Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars. Figure 1:…
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COBOSLAB: Cognitive Bodyspaces: Learning and Behavior:
Laboratory that investigates and models the Self-organized Learning of and Behavior within Integrated Multimodal Multimodular Bodyspace Representations.
Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution
Get the entire book! Introduction to Neural Networks with Java Programming Neural Networks in Java will show the intermediate to advanced Java programmer how to create neural networks. This book attempts to teach neural network programming through two mec
Neuroph is lightweight Java neural network framework to develop common neural network architectures. It contains well designed, open source Java library with small number of basic classes which correspond to basic NN concepts. Also has nice GUI neural network editor to quickly create Java neural network components. It has been released as open source under the LGPL license, and it's FREE for you to use it.
If you are starting with Neural Networks you should check out my online book on the subject. It contains over 300 pages of information on Neural Network Programming in Java. You can access it here.
In this project, we provide our implementations of CNN [Zeng et al., 2014] and PCNN [Zeng et al.,2015] and their extended version with sentence-level attention scheme [Lin et al., 2016] .
We introduce the Generative Query Network (GQN), a framework within which machines learn to perceive their surroundings by training only on data obtained by themselves as they move around scenes. Much like infants and animals, the GQN learns by trying to make sense of its observations of the world around it. In doing so, the GQN learns about plausible scenes and their geometrical properties, without any human labelling of the contents of scenes.
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Fraser, H.S.F., et al., “Differential diagnoses of the heart disease program have better sensitivity than Resident Physicians”, Tufts-New England Medical Center, Boston, MA(2001). 6. Mohammad Eid Alzaharani, Shaikh Abdul Hannan, “Diagnosis and Medical Prescription of Heart Disease Using FFBP, SVM and RBF”, Issue,1, Vol 5, , KKU Journal of Basic and Applied Sciences, Mar 2019 , Page 6-15. 7. Frawley and Piatetsky-Shapiro, 1996. Knowledge Discovery in Databases: An Overview. The AAAI/MIT Press, Menlo Park, C.A. 8. Aqueel Ahmed, Shaikh Abdul Hannan, “Data Mining Techniques to Find Out Heart Diseases: An Overview”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), An ISO 9001:2008 Certified International Journal, Volume-1, Issue-4, September 2012, ISSN: 2278-3075, New Delhi, India. 9. I. Turkoglu, A. Arslan, E. Ilkay, “An expert system for diagnosis of the heart valve diseases”, Expert Systems with Applications vol.23, pp. 229–236, 2002. 10. I. 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Woodcock, Neural network analysis of Doppler ultrasound blood low signals: a pilot study, Ultrasound in Medicine & Biology 23 (5) (1997) 683–690. 15. I. Guler, M.K. Kiymik, S. Kara, M.E. Yuksel, Application of autoregressive analysis to 20 MHz pulsed Doppler data in real time, International Journal Biomedical Computing 31 (3–4) (1992) 247–256. 16. Shaikh Abdul Hannan, "Heart Disease Diagnosis by using FFBP and GRNN algorithm of Neural Network", International Journal of Computer Science and Information Security, Vol 12, Number 6, June 2014, ISSN 1945-5500, United States of America. 17. Santosh K. Maher, Sumegh Tharewal, Abdul Hannan, “Review on HRV based Prediction and Detection of Heart Disease”, International Journal of Computer Applications (0975 – 8887), Pag 7-12, Volume 179 – No.46, June 2018. 18. https://www.who.int/en/news-room/fact sheets/detail/cardiovascular-diseases-(cvds) https://www.mayoclinic.org/diseases-conditions/stroke/symptoms-causes/syc-20350113. 19. Shaikh Abdul Hannan, “An Overview of Big Data and Hadoop”, International Journal of Computer Application”, Volume 154, Number 10, ISSN – 0975-887, November 2016, New York, USA. 20. Santosh Maher, Shaikh Abdul Hannan, Sumegh Tharewal, K. V. Kale " HRV based Human Heart Disease Prediction and Classification using Machine Learning " December 2019, (Vol. 17 No. 2 International Journal of Computer Science and Information SecApplicatiion (IJCA), New York, USA. 21. Akram Ablsubari, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, Rakesh Ramteke, "Composite Feature Extraction and Classification for Fusion of Palmprint and Iris Biometric Traits", Engineering Technology and Applied Science Research, (ETASR) Volume 9, No 1, Feb 2019, ISSN: 2241-4487, Greece. 22. Yogesh Rajput, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, D. Patil Ramesh Manza, Design and Development of New Algorithm for person identification Based on Iris statistical features and Retinal blood Vessels Bifurcation points” ” International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R), December 21-22, 2018, India. 23. Yogesh Rajput, Shaikh Abdul Hannan, “Design New Wavelet Filter for Detection and Grading of Non-proliferative Diabetic Retinopathy Lesions”, International Conference on Recent Trends in Image Processing and Pattern Recognition, Jan 2020, Springer, Singpore. 24. Y. M. Rajput, A. H. Hannan, M. E. Alzahrani, R. R. Manza, D. D. Patil, “EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques–A Review”, International Journal of Computer Sciences and Engineering, Vol 6, Issue 9, Sep 2018. 25. Shaikh Abdul Hannan, Bharatratna P. Gaikwad, Ramesh Manza, "Brain Tumor from MRI Images : A Review". 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Haralambos Sarimveis, Philip Doganis, Alex Alexandridis, “A classification technique based on radial basis function neural networks”, Advances in Engineering Software vol.37, pp.218–221, 2006. 37. Chauvin in, Y and D.E. Ruumehart Backpropagation : Theory, Architechtures and Applications, Erbaum Mahwah, NJ, ISBN : 080581258. PP 561, 1995. 38. Shaikh Abdul Hannan, V. D. Bhagile, R.R. Manza, R. J. Ramteke, “Heart Disease Diagnosis By Using FFBP algorithm of Artificial Neural Network”, International Conference on Communication, Computation, Control and Nanotechnology, ICN-2010 Organized by Rural Engineering College Bhalki-585328, during October 29-30, 2010. 39. Cigizoglu HK, Alp M. Generalized regression neural network in modelling river sediment yield. Adv Eng Software 2005;37:63–8. 40. Kim B, Lee DW, Parka KY, Choi SR, Choi S. Prediction of plasma etching using a randomized generalized regression neural network. Vacuum 2004;76:37–43 41. Jang JSR, Sun CT, Mizutani E. Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, Upper Saddle River, New Jersey, USA; 1997 Chapter 9. 42. Shaikh Abdul Hannan, R. R. Manza and R.J. Ramteke, “Association Rules for Filtering The Medicine To Avoid Side Effects Of Heart Patients”, on 16 -19 Dec 2009, at Advances in Computer Vision and Information Technology – 09, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. 43. Anupriya Kamble, Abdul Hannan, Yogesh, Dnyaneshwari, “Association detection of Regular Insulin and NPH Insulin Using Statistical Features”, Second International Conference on Cognitive Knowledge Engineering, 21-23 December 2016 (ICKE-2016), Aurangabad, Maharashtra, India, pp 59-62, ISBN 978-93-80876-89-4. 44. Shaikh Abdul Hannan, Pravin Yannawar, R. R. Manza and R.J. Ramteke, “Data Mining Technique for Detection of Cardiac Problems Using Symptoms Medicine and Its Side effects”, in IT & Business Intelligence -09 , in IT & Business Intelligence, on 06-08 Nov 2009, Organized By IMT, Nagpur, India. 45. Shaikh Abdul Hannan, Jameel Ahmed, Naveed Ahmed, Rizwan Alam Thakur, “Data Mining and Natural Language Processing Methods for Extracting Opinions from Customer Reviews”, International Journal of Computational Intelligence and Information Security, pp 52-58, Vol. 3, No. 6, July 2012. ( ISSN: 1837-7823). 46. Ordonez C,” Association rule discovery with the train and test approach for heart disease prediction”, IEEE Transactions on Information Technology in Biomedicine, P(334 – 343), April 2006 47. 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