NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Classification")'

Oxford textbook of psychopathology /

New York : Oxford University Press, 2009 . xii, 826 p. : 26 cm.. 9780195374216 (cloth : alk. paper) | 0195374215 (cloth : alk. paper)

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Strickberger's evolution : the integration of genes, organisms and populations /

By Hall, Brian Keith,. Sudbury, Mass. : Jones and Bartlett, 2008 . xv, 760 p. : , Rev. ed. of: Evolution / Monroe W. Strickberger. 3rd ed. c2000. 29 cm.. 9780763700669 (alk. paper) | 0763700665 (alk. paper)

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Powder Technology Handbook.

New York : Marcel Dekker, 1997 . xxiii, 944 p. : 24 cm.. 0824700155 (hardcover : acidfree paper)

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A practitioner's guide to resampling for data analysis, data mining, and modeling /

By Good, Phillip I.. Boca Raton, FL : CRC Press, 2012 . x, 214 p. : 25 cm.. 9781439855508

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Applications of Supervised and Unsupervised Ensemble Methods /

By Okun, Oleg.. 9783642260773

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Unmanned Aerial Vehicles /

By Valavanis, Kimon P.. 2011 9789400711099

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Power equipment engine technology /

By Abdo, Edward.. Clifton Park, NY : Delmar/Cengage Learning, 2011 . 1 online resource (xii, 398 pages) : , Includes index. 9781418053888

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Sustainability in project management /

Burlington, VT : Gower Pub., 2012 . xviii, 164 p. : 24 cm.. 9781409431695 (pbk. : alk. paper)

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Solid state physics

By Ashcroft, Neil W.. New York, Holt, Rinehart and Winston 1976 . xxi, 826 p. 25 cm.. 0030839939

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The New Naturalist butterflies /

By Ford E.B. [Eng.] : Collins 1977 . xviii, 369 p. ; 23 cm.. 0900848944 :

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Image processing for remote sensing-(E-BOOK)

Boca Raton, FL : CRC Press/Taylor & Francis Group, 2008 . 380 s. 1-4200-6664-1 | 978-1-4200-6664-7

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CWSP Certified Wireless Security Professional Official Study Guide (E-Book) Exam PW0-204.

By Coleman, David D.. Hoboken : John Wiley & Sons, Inc., 2010 . 1 online resource (703 p.) , Description based upon print version of record. 978-0-470-61962-9

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Biomedical Engineering (E-Book)

By Carlos Alexandre Barros de Mello. India In-Teh 2009 . x,658 P;

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Data Mining in Medical and Biological Research (E-Book)

By Eugenia G. Giannopoulou. India In-Teh 2008 . viii,320 P;

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Intelligent and Biosensors (E-Book)

By Vernon S. Somerset. India In-Teh 2010 . 396 p;

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Recent Advances in Biomedical Engineering (E-Book)

By Dr Ganesh R Naik. India In-Teh 2009 . xii,660 P;

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Application of Machine Learning (E-Book)

By Yagang Zhang. India In-Teh 2010 . viii,280p;

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Bayesian Network (E-Book)

By Ahmed Rebai. India Sciyo 2010 . x,432p;

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Classification of brain cognitive activity using multimodal neuroimaging dataset

By Sarwat Fatima. Islamabad NUST-SEECS 2016 . 42p.

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Principles of water treatment /

Hoboken : Wiley, 2012 . xvii, 654 pages : , Includes index. 25 cm.. 9780470405383 (hardback)

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Introduction to Volume Rendering

By Barthold Lichtenbelt, Randy Crane, . [S.l.] : Prentice Hall, PTR 1998 . 236 p. ; 24 cm.. 0138616833 (hardcover) | 9780138616830 (hardcover)

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Market research in practice : how to get greater insight from your market /

By Hague, Paul N.. New Delhi Koganpage 2013 . xiii, 257 pages : , "First published in Great Britain and the United States in 2004."--T.p. verso. 24 cm.. 9780749468644 (pbk.) | 9780749468651 (ebook)

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Building structures /

By Ambrose, James E.. Hoboken, N.J. : Wiley, 2012 . xv, 528 p. : 29 cm.. 9780470542606 (hbk. : alk. paper)

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Electrical energy efficiency technologies and applications /

Chichester [England] ; | Hoboken, N.J. : Wiley, 2012 9781119990055 (ebook)

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Mathematical Models in Biology an introduction

UK Cambridge University press 2004 . 370 p. 0-521-61555-0

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Automated Segmentation and Classification of Lesion On Breast Ultrasound

By Zahra Fazal. Islamabad SMME NUST 2014 . 56 p. 30cm.

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Individual Differences in Producing Movement Related Potentials & Online Multiclass Brain-Computer Interface for Detection and Classification of Movement-Related Cortical Potentials Associated with Task Force and Speed /

By Navid, Muhammad Samran. Islamabad : SMME - NUST, 2015 . xvi, 75 p. : ill. ; , Hardcover. 30cm..

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Fundamentals of Materials Science and Engineering \ an integrated approach /

By Callister, William D.,. Hoboken, N.J. : Wiley, 2013 . xxv, 910 p. : , Includes index. 27 cm.. 9781118322697

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Water resources engineering /

By Wurbs, Ralph Allen.. Upper Saddle River, NJ : Prentice Hall, 2002 . x, 828 p. : 25 cm.. 0130812935

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Construction supply chain management :

By William J. O'Brien. London | CRC Press 2009 . xii, v p. : 25 cm..

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Foundation engineering /

By Hansbo, Sven,. Amsterdam ; | New York : Elsevier, 1994 . xviii, 519 p. : 25 cm.. 0444885498

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Steel designers' manual /

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Mathematics for machine learning

By Deisenroth, Marc Peter,. UK Cambridge University Press 2020 . 371p 9781108679930

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TH-SOF-1373-EEG signal classification for predicting the movement intent of lower limb

By Anjum Naeem Malik. Islamabad NUST College of EME 2017

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TH-SOF-1211-Brain Computer Interface Classification of EEG signals for Wrist and Grip using Emotiv

By Nasir Hussain. Islamabad NUST College of EME 2001

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TH-SOF-1233-Seizure Detection from the Time-Frequency Based Multichannel Newborn EEG Signal through the Application of Advanced Noise Filtering and Classification Methods

By MOIZ YUSAF, . Islamabad NUST College of EME 2016

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TH-SOF-1127-Development of a Robust System for Brain Tumor Classification in MRI.PDF

By Muhammad Nasir . Islamabad NUST College of EME 2014

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PR-SOF-1974-Brain Signal Processing for Improved Classification

By Nabeel Ahmad. Syed Muhammad Ammar Shah. Muhammad Azhar Saeed. Muhammad Talha Saeed.. ISLAMABAD NUST COLLEGE OF EME 2020

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It encyclopaedia.com,vol-4 computer networks and e-commerce

By Diwan, Parag Suri, R.K Kaushik, Sanjay. NEW DELHI PENTAGON PRESS 2001 . 598P 81-86830-18-9

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Machine Learning /

By Dutt, Saikat . Pearson India 2019 . 456 p.: ‎ 978-9353066697

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Fundamentals of digital image processing : a practical approach with examples in Matlab /

By Solomon, Chris.. Chichester, West Sussex ; | Hoboken, NJ : Wiley-Blackwell, 2011 . xiv, 328 p. : 25 cm.. 9780470844724 (hardback) | 9780470844731 (hbk.)

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An Efficient Deep Learning-Based Classification Framework for Hypertensive Retinopathy /

By Sajid, Muhammad Zaheer. . ix, 45 p

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TH-SOF-2174-Semi-Supervised Learning for Cancer Classification on BreakHis 400X

By MEHWISH MAJEED MALIK . ISLAMABAD NUST COLLEGE OF EME 2023

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Early Detection & Stage Classification of Parkinson’s Disease using Deep Learning /

By Zeeshan, Muhammad Muzzamil . . 38p. ; 30cm..

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Diagnosing and localizing Covid-19 in High resolution CT(HRCT) scans using Deep learning /

By Munir, Zonaira. . 62p. ; 30cm..

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Automatic Detection and Recognition of Citrus Fruits Diseases Using Deep Learning Model /

By Faisal, Shah . . 59p. , In a country's economy, agriculture plays a very vital role. Agriculture's yield and production are reduced by plant diseases, resulting in significant economic losses and instability in the food market. In plants, the citrus fruit crop is one of the most important agricultural products in the world, produced and grown in around 140 countries. It has a lot of nutrients, such as vitamin C. However, due to pests and diseases, citrus cultivation is widely affected and suffers significant losses in both yield and quality. The majority of plant diseases exhibit visible symptoms, and the accepted method used today is for a skilled plant pathologist to detect the diseases by examining affected plant leaves under a microscope, which is a costly and time-consuming method. During the last decade, computer vision and machine learning have been widely adopted to detect and classify plant diseases, providing opportunities for early disease detection and bringing improvements to agricultural production. The early detection and accurate diagnosis of plant diseases are essential for reducing their spread and damage to crops. In this work, we presented an automatic system for early detection and recognition of citrus plant diseases based on a deep learning (DL) model to improve accuracy and reduce computational complexity. The most recent transfer learning-based models were applied to our dataset in order to increase classification accuracy. In this work, we successfully proposed a CNN-based pre-trained model (EfficientNetB3, ResNet50, MobiNetV2, (InceptionV3) for the identification and classification of citrus plant diseases using transfer learning. In order to assess the performance of the model, we found that the transfer of an EfficientNetb3 model led to the highest training, validating, and testing accuracies, which were 99.43%, 99.48%, and 99.58%, respectively. The proposed CNN model exceeds other cutting-edge CNN network architectures developed in earlier literature in the identification and categorization of citrus plant diseases. 30cm.

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FNIRS DATA CLASSIFICATION FOR BRAIN COMPUTER INTERFACE USING DEEP LEARNING /

By SUBHANI , AHMAD . . 67p. ; 30cm..

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Decoding of Hand Motion Using State of Art Time Domain, Frequency Domain And Feature Extraction /

By Munawar, Sulaiman . . 69p. , Exoskeletons that are activated by the muscles and brain have been suggested to train the motor skills of stroke victims. Training can incorporate task variety since an exoskeleton allows for the execution of various movement types.Differentiating between movement types at the same time from brain activity is challenging, but it might be accessible from residual muscular activity that many patients retain regain.This study examines whether forearm EMG from five stroke patients can be used to decode seven distinct motion classes of the hand and forearm. This study evaluates classifiers like Support vector machine (SVM), Lineardiscriminant analysis (LDA) and K nearest neighbor (KNN). It investigated the relation of motor impairment with classification accuracy by the classifiers. During the following motion classes: Supination, Pronation, Hand Close, Hand Open, Wrist Extension, Wrist Flexion, and Pich, five surface EMG channels were recorded.Every motion was performed by patients three times repetition over the course of eight weeks.Support vector machines, k nearest neighbor, and linear discriminant analysis were used to classify decoding of hand moments for stroke patients. On average,73.69 ± 6.39%SVM,71.6 ± 5.09% KNNand 50±4.56 LDA of the movements were correctly classified.Seven motion classes were demonstrated to be decoded from residual EMG, and SVM proved to be the most effective classification method when compared to the other three classifiers for decoding of hand motion for stroke patients.The results of this study may have implications for the development of exoskeletons, suits, or gadgets, that are powered by EMG signals. These devices might be utilized in the comfort of the patient's home to assist stroke sufferers with their training activities. Therefore, the findings of this study may assist in improving the effectiveness and accessibility of these useful tools for stroke survivors. 30cm.

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Stream Classification & Brand Recognition for Media Analysis /

By Ijaz, M Adeel . . 55p. 30cm.

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A Novel Approach to Breast Tumor Classification /

By Ikram Mughal, Mehwish. . 93,p; 30,cm..

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