Ashish Thakur

Vignan's Foundation for Science, Technology & Research

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Sanjeet Kumar Bhagat

Vignan's Foundation for Science, Technology & Research

Chetan Kamble

Vignan's Foundation for Science, Technology & Research

Thorati Som Bhusan

Vignan's Foundation for Science, Technology & Research

Thirumalasetty Sai

Vignan's Foundation for Science, Technology & Research

R. S. Anand

Indian Institute of Technology Roorkee

Pola Chaitanya Nikhil

Vignan's Foundation for Science, Technology & Research

Bandi Raja Babu

SRM University

Vinita Jain

Jajula Ravi Teja

Vignan's Foundation for Science, Technology & Research

Himanshu Kumar Shekhar

Homi Bhabha National Institute

Cooperative Institutions

Vignan's Foundation for Science, Technology & Research

Indian Institute of Technology Roorkee

Amrita Vishwa Vidyapeetham

Aalborg University

Texas Instruments (United States)

Texas Instruments (India)

Indian Institute of Technology Kanpur

Chhatrapati Shahu Ji Maharaj University

Indian Institute of Technology Indore

Indian Institute of Technology Dhanbad

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A Local Statistics Based Region Growing Segmentation Method for Ultrasound Medical Images

World Academy of Science, Engineering and Technology, International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering (2007)

Ashish Thakur Radhey Shyam Anand

Region growing

Medical ultrasound

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Citations (30)

Application of Recurrence Quantification Analysis for Non-Linear Dynamical Systems

International Journal of Engineering and Advanced Technology (2019)

Himanshu Kumar Shekhar Chetan Kamble Ashish Thakur Sanjeet Kumar Bhagat

The Recurrence plots (RPs) have been introduced in several different scientific and medical disciplines. The main purpose of recurrence plot is used to of identify the higher dimensional phase space trajectories. RPs are purely graphically representation which have been designed for the detection of hidden dynamical patterns and non-linearity present in the data, the evaluation of error which is caused by observational noise can be done by Recurrence Quantification Analysis (RQA). RQA method is initially used to minimize the error present in the given signals. RQA method is a basically a technique for the analysis of nonlinear data to quantify the number and duration of a dynamical systems. The recurrence plot is used for time series domain for multidimensional signal also. Recurrence is the property of non-stationary and dynamical system to characteristics the time series analysis in phase space trajectories. Recurrence Quantification Analysis is used to derive from recurrence plots, which are based upon distances matrices of time series.

Recurrence quantification analysis

Recurrence plot

Plot (graphics)

Dynamical system (definition)

Representation

10.35940/ijeat.a1010.1291s519

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Comparative Analysis of FIR Filter Design using Different Multipliers and CLA adder

International Research Journal of Modernization in Engineering Technology and Science (2023)

Goutham Gudipudi Pola Chaitanya Nikhil Thirumalasetty Sai Ashish Thakur

A comparative analysis study of FIR filter implementation reveals that employing various multiplier design strategies can help identify a high-quality response filter from a range of FIR filters.The significance of filters stems from the rapid growth of communication systems in recent times, as they play a crucial role in these systems.Filters are extensively utilized in digital signal processing applications to achieve objectives such as noise reduction, signal amplification, and data compression.Their primary purpose is to enable the recovery of the original signal at the receiver side, allowing for effective communication.Even if the filtered output is relatively small, a strong filtered signal can be sent to an amplifier to restore the original signal.To achieve this, it is essential for the filter to be both efficient and well-designed.Given the increasing number of communication systems, selecting the right filter becomes paramount to ensure optimal performance and maintain the integrity of the transmitted signal.By comparing the implementation stats of various FIR filters and considering different multiplier design strategies, it is possible to identify a high-quality response filter.Such a filter will contribute to the effective functioning of communication systems by enabling noise reduction, signal amplification, and data compression, ultimately leading to successful signal recovery at the receiver end.

Finite impulse response

10.56726/irjmets42181

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INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY CREDIT CARD FRAUD DETECTION USING HIDDEN MARKOV MODEL AND ENHANCED SECURITY FEATURES

Ashish Thakur Bushra Shaikh Vinita Jain

The most accepted payment mode is credit card for both offline and online in today’s world, it will provide cashless shopping at every shop across the world. It will be the most suitable way to do online shopping, paying bills, and performing other related tasks. Hence risk of fraud transactions using credit card has also been increasing. In the prevailing credit card fraud detection processing system, fraudulent transaction will be detected after transaction is done. It is difficult to find out fraudulent and regarding losses will be barred by issuing authorities. Hidden markov mode is the statistical tools for engineers and scientists to solve various problems. Credit card fraud can be detected using hidden markov model during transactions. Hidden markov model aids to obtain a high fraud transaction coverage combined with low false alarm rate, thus providing a better and convenient way to detect frauds. Using hidden markov model, customer’s pattern is analyzed and any deviation from the regular pattern is considered to be a fraudulent transaction. So in our project we will be using hidden markov model to detect fraudulent transaction.

Credit card fraud

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Application of Recurrence Quantification Analysis for Non-Linear Dynamical Systems

International Journal of Engineering and Advanced Technology (2019)

Himanshu Kumar Chetan Kamble Ashish Thakur K. C. Bhagat Sanjeet Kumar Bhagat

Recurrence quantification analysis

Recurrence plot

Plot (graphics)

Dynamical system (definition)

Representation

10.35940/ijeat.a1010.1291s52019

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Image quality based comparative evaluation of wavelet filters in ultrasound speckle reduction

Digital Signal Processing (2005)

Ashish Thakur R. S. Anand

Non-Local Means

Stationary wavelet transform

Speckle noise

Peak signal-to-noise ratio

Second-generation wavelet transform

10.1016/j.dsp.2005.01.002

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Citations (57)

FPGA Based on Voting System along with Cross Voters Detection

Bandi Raja Babu Jajula Ravi Teja Thorati Som Bhusan Addanaki Janardhan Ashish Thakur

This article presents the FPGA Based on Voting System along with Cross Voters Detection using Python. The proposed system consists of three modules, namely the Vote Monitoring Module (VMM), Image Acquisition Module (IAM) and Image Detection Module, for casting and knowing the result of the election, image capturing purpose and Detecting the cross voters using facial recognition respectively. The Voting Unit (VMM) unit is implemented on FPGA(Zed board- ZYNQ 7000) using Verilog in such a way that consists three modules namely Button control module, Vote logger module and mode control. Button control module is used for casting the vote and knowing the result of each candidate. Mode control is used to choose the mode whether it is in voting mode or result mode and vote logger module is used to store the votes of each candidate separately. The Image acquisition module is used to detect the motion of the voter capture his face and vote casting image and that it sends to dedicated server for backup purpose and cross checking purpose. Simultaneously Image Detection Module (IDM) unit is used to check the cross voter images if it finds any cross voter face those will be removed and respective votes will treat as invalid votes. Those invalid votes will remove from genuine votes.

Python

10.1109/temsmet56707.2023.10150091

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FEATURE EXTRACTION IN ULTRASOUND MEDICAL IMAGES

Ashish Thakur

Feature (linguistics)

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Citations (22)