POTLADURTY SURESH BABU

@svce.edu.in

Associate Professor and ECE
Sri Venkateswara College of Engineering

POTLADURTY SURESH BABU


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https://researchid.co/sureshbabu413

EDUCATION

Ph.D in Signal Processing
M.Tech in Electronics Instrumentation and Communication Systems
B.Tech in Electronics and Communication Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Signal Processing, Electrical and Electronic Engineering, Computer Science, Artificial Intelligence
12

Scopus Publications

46

Scholar Citations

4

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Remote sensing and machine learning approaches for heat island mapping and analysis: a review and framework for sustainable smart cities
    Venkata Sudhakar Chowdam, Venkata Naresh M, Ganjikunta Ganesh Kumar, Suresh Babu Potladurty
    Environment Development and Sustainability, 2026
  • Hybrid Deep Learning and Metaheuristic Optimization for Multi-Class Knee Osteoarthritis X-ray Classification
    Potladurty Suresh Babu, Koyyana Yashwanth, Mendu Anusha, Uma Maheswari Rayudu, Srinivasa Raju Yarakaraju, Naladi Ram Babu
    Proceedings of 6th International Conference on Expert Clouds and Applications Icoeca 2026, 2026
    Accurate assessment of knee osteoarthritis (OA) severity from X-ray images is essential for early diagnosis and effective treatment planning. However, reliable multi-class classification of Kellgren–Lawrence (KL) grades remain challenging due to subtle visual differences between adjacent severity levels. This paper proposes a hybrid framework that integrates deep learning baselines, transformer-based feature representation, and metaheuristic feature optimization for knee OA severity classification. Initially, two end-to-end convolutional neural network models—a lightweight custom CNN and ResNet18—are employed as baseline classifiers to establish reference performance. Subsequently, a pretrained Vision Transformer is utilized as a feature extractor to obtain global image representations from knee X-ray images. To further enhance discriminative capability, Harris Hawks Optimization (HHO) is applied to select an optimal subset of ViT features. The optimized features are classified using conventional machine learning models, including Support Vector Machine, Extra Trees, and Gradient Boosting. Experimental results on a publicly available knee osteoarthritis X-ray dataset demonstrate that the proposed ViT + HHO framework consistently outperforms CNN baselines and non-optimized ViT-based models, achieving improved accuracy and Macro-F1 scores. The results confirm the effectiveness of combining transformer-based representation learning with metaheuristic optimization for robust multi-class knee osteoarthritis severity classification.
  • Solvothermal synthesis and electrochemical performance of BiOBr nanosheets for symmetric supercapacitor devices
    Potladurty Suresh Babu, Reddi Mohan Naidu Kalla, Sreedhar Doraswamy, Jaewoong Lee, Sivarama Krishna Lakkaboyana, Salah Knani, Seepana Praveenkumar, Reem Alreshidi
    Scientific Reports, 2025
    Bismuth-containing compounds have attracted considerable interest in electrochemical energy storage owing to their distinctive layered structures and favorable redox features. However, systematic studies on bismuth oxybromide (BiOBr) as an electrode materials for supercapacitors remain limited, despite its promising layered architecture that an facilitate ion transport and offer abundant active sites. In this study, we report the solvothermal preparation of BiOBr nanostructures with a unique curved sheet-like morphology, specifically designed to improve electrochemical activity. The fabricated BiOBr electrode demonstrated a high capacity of 84.6 mAh/g at 1.1 A/g, along with notable cycling stability. Furthermore, the assembled symmetric supercapacitor exhibited a notable energy density (Ed) of 10 Wh/kg at a power density (Pd) of 750 W/kg, while retaining 98% of its original capacitance over 3000 continuous runs. These findings highlight the potential of BiOBr-based electrodes as effective and durable materials for next-generation supercapacitor technologies.
  • Design and evaluation of clock-gating-based approximate multiplier for error-tolerant applications
    Chowdam Venkata Sudhakar, Suresh Babu Potladurty, Prasad Reddy Karipireddy
    International Journal of Reconfigurable and Embedded Systems, 2025
    The multiplier is an essential component in real-time applications. Even though approximation arithmetic affects output accuracy in multipliers, it offers a realistic avenue to constructing power area and speed-efficient digital circuits. The approximation computing technique is commonly used in error-tolerant applications such as signal, image, and video processing. In this paper, approximate multipliers (AMs) are designed using both conventional and approximate half adders (A-HA) and full adders (A-FA), which are strategically placed to add partial products at the most significant bit (MSB) positions, and OR gates are used to add partial products at the lower significant bit (LSB). In addition, this research article demonstrates unsigned and signed multipliers using the ripple carry adder (RCA), carry save adder (CSA), conditional sum adder (COSA), carry select adder (CSLA), and clock gating technique. The proposed multipliers are implemented in Verilog hardware description language (HDL) and simulated on the Xilinx VIVADO 2021.2 design tool with target platform Artix-7 AC701 FPGA. The simulation results found that unsigned and signed approximate multiplier power consumption was reduced by 13% and 18.18% respectively and enhanced accuracy.
  • Design and evaluation of clock-gating-based approximate multiplier for error-tolerant applications
    Venkata Sudhakar Chowdam, Suresh Babu Potladurty, Prasad Reddy karipireddy
    Memories Materials Devices Circuits and Systems, 2025
    The multipliers are essential components in real-time applications. Although approximation arithmetic affects the output accuracy in multipliers, it offers a realistic avenue for constructing power-, area--, and speed-efficient digital circuits. The approximation computing technique is commonly used in error-tolerant applications such as signal, image, and video processing. In this study, approximate multipliers (AMs) are designed using both conventional and approximate half adders (A-HAs) and full adders (A-FAs), which are strategically placed to add partial products at the most significant bit (MSB) positions, and OR gates are used to add partial products at the lower significant bit (LSB). In addition, this research article demonstrates unsigned and signed multipliers using the Ripple Carry Adder (RCA), Carry Save Adder (CSA), Conditional Sum Adder (COSA), Carry Select Adder (CSLA), and Clock Gating Technique. The proposed multipliers are implemented in Verilog HDL and simulated on the Xilinx VIVADO 2021.2 design tool, with the target platform being the Artix-7 AC701 FPGA. The results found that the power dissipation change is 13%, the delay change is 4.7%, and the area change is 15% for the 16-bit unsigned approximate multiplier. For the 16-bit signed approximate multiplier, the power change is 18.81%, the delay change is 3.57%, and the area change is 14.29% using inexact and exact adders and the clock gating technique with CSA as the final partial product summer. Clock-gating 16-bit multiplier RED decreases when compared to approximate adder usage alone in the multiplier. The proposed multipliers are useful in error-tolerant applications such as digital signal processing, image fusion, image blending, smoothing, and sharpening to produce high-quality images at high speed and with low power consumption.
  • Optimal distributed generator placement for loss reduction using fuzzy and adaptive grey wolf algorithm
    Daruru Sarika, Palepu Suresh Babu, Pasala Gopi, Manubolu Damodar Reddy, Suresh Babu Potladurty
    International Journal of Applied Power Engineering, 2025
    This research provides a new methodology for locating distributed generation (DG) units in distribution electrical networks utilizing the fuzzy and adaptive grey wolf optimization algorithm (AGWOA) to decrease power losses and enhance the voltage profile. Everyday living relies heavily on electrical energy. The promotion of generating electrical power from renewable energy sources such as wind, tidal wave, and solar energy has arisen due to the significant value placed on all prospective energy sources capable of producing it. There has been substantial research on integrating distributed generation into the electricity system due to the growing interest in renewable sources in recent years. The primary reason for adding distributed generation sources for the network is to supply a net quantity of power, lowering power losses. Determining the amount and location of local generation is crucial for reducing the line losses of power systems. Numerous studies have been conducted to determine the best location for distributed generation. In this study, DG unit placement is determined using a fuzzy technique. In contrast, photovoltaic (PV) and capacitor placement and size are determined simultaneously using an adaptive grey wolf technique based on the cunning behavior of wolves. The proposed method is developed using the MATLAB programming language; the results are then provided after testing on test systems with 33-bus and 15-bus.
  • Evaluating ILD designs in HRCT images using deep learning
    K. Praveena, P. Divyasree, P. Rajesh, M. K. Tharun, P. Babu
    Aip Conference Proceedings, 2024
  • Adaptive PCA-Based Spectral Estimation Method for MST Radar Signal Processing
    G. Chandraiah, P.Suresh Babu, G. Srinivasulu
    2024 International Conference on Wireless Communications Signal Processing and Networking Wispnet 2024, 2024
    Subspace methods founded on Eigen-value decomposition have been utilized to retrieve relevant data from extensive datasets. This work suggests the least variance spectral estimation technique named as Proposed Algorithm (PALG) for adaptive principle component based spectrum computation. Using PALG, we analyze the signal received by the MST (Mesosphere-Stratosphere-Troposphere) radar placed at NARL (National Atmospheric Research Laboratory) Gadanki in this proposed work. Additionally, we tested the PALG approach with simulated signals, like broadband signals, at various noise levels (a). The PALG performed better in identifying the number of frequencies in the simulated signal, especially in the case of a noise-corrupted signal. Finally, the suggested algorithm is applied to the MST radar data in order to estimate the Doppler frequency spectrum, which is then utilized to determine the wind, zonal, and meridional velocities. The PALG performs well at higher altitudes when compared to current techniques, and ground truth GPS data was used to validate the MST radar results.
  • Efficient Approximate Adders for Image Processing Applications
    C. Padma, Suresh Babu Potladurty, C. Nalini, T. Suguna, CH. Pallavi
    2024 International Conference on Advances in Computing Research on Science Engineering and Technology Acroset 2024, 2024
    This effort sacrificed accuracy in order to design fast, energy-efficient adders. In order to minimize propagation delay and reduce power consumption, the proposed design truncates half of the adder area. Additionally, internal stage input-output pipelining to the parallel prefix adder can further optimize propagation delay to half of its original value. By significantly raising the approximation adder error, the MSP minimizes the parameters while utilizing the exact calculation and LUTs as resources. In comparison to the current LEADx and APEx, our proposed adder is now efficient in terms of parameters. Xilinx Vivado is used to synthesize the design, simulation, and efficacy of the suggested method. As a case study, the suggested approximation adders are applied in a video encoding application. For video encoding applications, LEADx provided superior quality when compared to other types of approximation adders. Thus, our suggested approximate adders can be useful in efficient FPGA designs of error-tolerant applications.
  • Facial Sentiment Analysis: Enhancing Emotion Recognition Through Advanced Convolutional Neural Network Architectures
    Daruru Sarika, Palepu Suresh Babu, Potladurthy Suresh Babu, Pasala Gopi, S. Venkateswarlu, P.B. Chennaiah
    2024 1st International Conference on Innovations in Communications Electrical and Computer Engineering Icicec 2024, 2024
    The domain of Computer Vision has observed the emergence of Facial Sentiment Analysis as a critical area, elucidating human emotions expressed through facial features. This investigation focuses on emotion recognition, specifically emphasizing the utilization of advanced Convolutional Neural Network (CNN) architectures to enhance the precision and efficacy of sentiment analysis. Despite considerable advancements, robust development of facial emotion recognition systems encounters persistent challenges. A primary hurdle involves addressing the inherent variability in human facial expressions, shaped by cultural, individual, and contextual influences. Overcoming the complexities associated with cross-cultural and cross-demographic generalization demands innovative solutions. Additionally, the scarcity of extensive and diverse annotated datasets poses a challenge in building highly generalized models. This study explores strategies to tackle these challenges, employing transfer learning techniques and data augmentation methods to bolster model generalization. Furthermore, the application of facial sentiment analysis in real-world scenarios necessitates models that not only ensure accuracy but also provide interpretability and explanation. The research delves into methods to enhance model interpretability, offering insights into the decision-making processes of neural networks, thereby fostering trust and acceptance in practical applications. Through a comprehensive examination of these challenges, this research contributes to the ongoing advancement in facial sentiment analysis, paving the way for more reliable and universally applicable emotion recognition systems.
  • Lifting Wavelets with OGS for Doppler Profile Estimation
    Potladurty Suresh Babu, Dr. G. Sreenivasulu
    International Journal of Electrical and Electronics Research, 2023
  • Mesosphere stratosphere troposphere (MST) radar signal using discrete wavelet transform with overlapping group shrinkage
    International Journal of Advanced Science and Technology, 2019

RECENT SCHOLAR PUBLICATIONS

  • Remote sensing and machine learning approaches for heat island mapping and analysis: a review and framework for sustainable smart cities
    VS Chowdam, VN M, GG Kumar, SB Potladurty
    Environment, Development and Sustainability, 1-34 , 2026
    2026
  • Design and evaluation of clock-gating-based approximate multiplier for error-tolerant applications
    VS Chowdam, SB Potladurty
    Memories-Materials, Devices, Circuits and Systems 9, 100123 , 2025
    2025
    Citations: 11
  • Optimal distributed generator placement for loss reduction using fuzzy and adaptive grey wolf algorithm
    D Sarika, PS Babu, P Gopi, MD Reddy, SB Potladurty
    International Journal of Applied 14 (1), 155-162 , 2025
    2025
    Citations: 1
  • Analyzing Glucose Levels through Image Processing and Deep Learning Methods
    A Aruna, SB Potladurty
    International Journal of Scientific Research in Science and Technology 11 (6 … , 2024
    2024
  • Efficient approximate adders for image processing applications
    C Padma, SB Potladurty, C Nalini, T Suguna, CH Pallavi
    2024 International Conference on Advances in Computing Research on Science … , 2024
    2024
    Citations: 5
  • Adaptive PCA-based spectral estimation method for MST radar signal processing
    G Chandraiah, PS Babu, G Srinivasulu
    2024 International Conference on Wireless Communications Signal Processing … , 2024
    2024
    Citations: 1
  • Lifting Wavelets with OGS for Doppler Profile Estimation
    DGS Potladurty Suresh Babu
    International Journal of Electrical and Electronics Research 11 (4), 933-938 , 2023
    2023
  • Denoising of MST RADAR Signal usingCWT and Overlapping Group Shrinkage
    PS Babu, G Sreenivasulu
    Turkish Journal of Computer and Mathematics Education 12 (5), 714-718 , 2021
    2021
    Citations: 2
  • Spectral Estimation of MST Radar Data using IAP
    SB POTLADURTY, DG SREENIVASULU
    INTERNATIONAL JOURNAL OF RESEARCH IN ELECTRONICS AND COMPUTER ENGINEERING 7 … , 2019
    2019
  • Mesosphere Stratosphere Troposphere (MST) Radar Signal using Discrete wavelet Transform with Overlapping Group Shrinkage
    SB POTLADURTY, DG SREENIVASULU
    International Journal of Advanced Science and Technology 28 (9), 133-136 , 2019
    2019
    Citations: 4
  • A Neoteric method of Object Extraction Based on Linear Discriminant Analysis
    A ARUNA, PS BABU
    INTERNATIONAL JOURNAL OF RESEARCH 7 (10), 666-674 , 2018
    2018
  • Trainable Nonlinear Reaction Diffusion (TNRD) based Low Light Image Enhancement
    MU Swathi, PS Babu
    International Journal of Scientific Research in Science, Engineering and … , 2018
    2018
  • Smart school bus for children transportation safety enhancement with iot
    P Ambedkar, PS Babu
    international Journal of Innovative Research in Computer and Communication 5 (7) , 2017
    2017
    Citations: 8
  • Ultrasonic Signal Processing Using FPGA
    K A, SB Potladurty
    IJAERS, 82-87 , 2017
    2017
    Citations: 1
  • ALGORITHMS FOR THE ANALYSIS OF MST RADAR SIGNALS - A SURVEY
    DGS P.Suresh Babu
    i-manager’s Journal on Digital Signal Processing 5 (3), 40-44 , 2017
    2017
  • Design and Development of Portable Power Charger
    P MADHU, PS BABU
    2017
  • A Novel Improved Irrigation System using Image Processing And Wireless Technology
    KSP REDDY, PS BABU
    2016
  • DESIGN AND SIMULATION OF LOW POWER FULL SUBTRACTOR USING GATE DIFFUSION INPUT (GDI)
    Y GM, SB POTLADURTY
    IJVESP 2 (4), 1-4 , 2016
    2016
  • Efficient Face Recognition Under Motion, Blur, Pose & Illumination Conditions
    SBP M Neelima
    IJVESP 2 (3), 1-3 , 2016
    2016
  • Real-Time Based Drinking Water Quality Monitoring and Contamination Detection System Using Low cost Sensor Network
    SBP B.Keerthi
    IJR 2 (10), 143-148 , 2015
    2015

MOST CITED SCHOLAR PUBLICATIONS

  • Design and evaluation of clock-gating-based approximate multiplier for error-tolerant applications
    VS Chowdam, SB Potladurty
    Memories-Materials, Devices, Circuits and Systems 9, 100123 , 2025
    2025
    Citations: 11
  • Speech Signal Analysis Using Windowing Techniques
    DPVNR Suresh Babu Potladurty,Dr.D.Srinivasulu Reddy
    IJETER 3 (6), 257-263 , 2015
    2015
    Citations: 9
  • Smart school bus for children transportation safety enhancement with iot
    P Ambedkar, PS Babu
    international Journal of Innovative Research in Computer and Communication 5 (7) , 2017
    2017
    Citations: 8
  • Efficient approximate adders for image processing applications
    C Padma, SB Potladurty, C Nalini, T Suguna, CH Pallavi
    2024 International Conference on Advances in Computing Research on Science … , 2024
    2024
    Citations: 5
  • Mesosphere Stratosphere Troposphere (MST) Radar Signal using Discrete wavelet Transform with Overlapping Group Shrinkage
    SB POTLADURTY, DG SREENIVASULU
    International Journal of Advanced Science and Technology 28 (9), 133-136 , 2019
    2019
    Citations: 4
  • A High-Performance VLSI Architecture for Image Compression Technique Using 2-D DWT
    S Jayachandranath, PS Babu
    International Journal of Engineering Research and Applications (IJERA) 2 (6 … , 2012
    2012
    Citations: 3
  • Denoising of MST RADAR Signal usingCWT and Overlapping Group Shrinkage
    PS Babu, G Sreenivasulu
    Turkish Journal of Computer and Mathematics Education 12 (5), 714-718 , 2021
    2021
    Citations: 2
  • Optimal distributed generator placement for loss reduction using fuzzy and adaptive grey wolf algorithm
    D Sarika, PS Babu, P Gopi, MD Reddy, SB Potladurty
    International Journal of Applied 14 (1), 155-162 , 2025
    2025
    Citations: 1
  • Adaptive PCA-based spectral estimation method for MST radar signal processing
    G Chandraiah, PS Babu, G Srinivasulu
    2024 International Conference on Wireless Communications Signal Processing … , 2024
    2024
    Citations: 1
  • Ultrasonic Signal Processing Using FPGA
    K A, SB Potladurty
    IJAERS, 82-87 , 2017
    2017
    Citations: 1
  • Denoising of Spectral Data Using Complex Wavelets
    C Madhu, PS Babu, S Jayachandranath
    system 2 (5) , 2012
    2012
    Citations: 1
  • Remote sensing and machine learning approaches for heat island mapping and analysis: a review and framework for sustainable smart cities
    VS Chowdam, VN M, GG Kumar, SB Potladurty
    Environment, Development and Sustainability, 1-34 , 2026
    2026
  • Analyzing Glucose Levels through Image Processing and Deep Learning Methods
    A Aruna, SB Potladurty
    International Journal of Scientific Research in Science and Technology 11 (6 … , 2024
    2024
  • Lifting Wavelets with OGS for Doppler Profile Estimation
    DGS Potladurty Suresh Babu
    International Journal of Electrical and Electronics Research 11 (4), 933-938 , 2023
    2023
  • Spectral Estimation of MST Radar Data using IAP
    SB POTLADURTY, DG SREENIVASULU
    INTERNATIONAL JOURNAL OF RESEARCH IN ELECTRONICS AND COMPUTER ENGINEERING 7 … , 2019
    2019
  • A Neoteric method of Object Extraction Based on Linear Discriminant Analysis
    A ARUNA, PS BABU
    INTERNATIONAL JOURNAL OF RESEARCH 7 (10), 666-674 , 2018
    2018
  • Trainable Nonlinear Reaction Diffusion (TNRD) based Low Light Image Enhancement
    MU Swathi, PS Babu
    International Journal of Scientific Research in Science, Engineering and … , 2018
    2018
  • ALGORITHMS FOR THE ANALYSIS OF MST RADAR SIGNALS - A SURVEY
    DGS P.Suresh Babu
    i-manager’s Journal on Digital Signal Processing 5 (3), 40-44 , 2017
    2017
  • Design and Development of Portable Power Charger
    P MADHU, PS BABU
    2017
  • A Novel Improved Irrigation System using Image Processing And Wireless Technology
    KSP REDDY, PS BABU
    2016