Center of Excellence for Signal Processing and Machine Learning (CoESPML)
About the Center of Excellence:
Welcome to the Centre of Excellence for Signal Processing and Machine Learning (CoE SPML) in the Department of Electronics and Communication Engineering. CoE SPML is an organized research unit founded in November 2022 that serves as a focus for quality research in signal processing, machine learning, data science, sensors data, speech/image/video processing, digital systems using machine learning and data fusion techniques. At CoE SPML, we are trying to explore both theoretical and practical frameworks for optimal data analysis in the research fields.
The Center of Excellence was formed as a specialized group to coordinate advanced research in all aspects of signal processing artificial intelligence, sensor systems, speech/image/video analysis, signal processing and machine learning, and to facilitate collaboration and interaction with industry sponsors and federal government research agencies.
The Center of Excellence for Signal Processing and Machine Learning is a hub for cutting-edge research and innovation. Our multidisciplinary team collaborates with academia, industry, and government to advance AI technologies. We focus on impactful projects, bridging the gap between research and practical applications. Through training programs, we nurture the next generation of AI talent. We uphold open science principles, sharing code, datasets, and knowledge with the global community to accelerate progress in signal processing and machine learning.
Name of Coordinator:Dr.P.Chandrasekhar
Designation:Asst. Prof.
Email:chandrasekhar@gnits.ac.in
Objectives:
To develop and implement educational programs to cultivate skills and expertise in signal processing and machine learning for faculty and students.
To conduct cutting-edge research in speech, image, video, and IoT systems using signal processing and machine learning algorithms by faculty and students.
To foster strong collaborations with academia, industry, and government for accelerated knowledge exchange and practical solution
To do projects addressing tangible applications, using AI to solve complex challenges across various industries or government agencies.
To collaborate actively with industry partners to seamlessly integrate research outcomes into practical applications.
To share research findings, code, datasets, and publications openly to contribute to the global community and accelerate progress in the field.
Faculty associated with Centre of Excellence for Signal Processing and Machine Learning
| S.No | Nameof thefaculty | Designation | Qualification | Areaofresearch |
| 1 | Dr. P. Chandrasekhar | Asst.Prof. | Ph.D. | Acoustic Scene Classification |
| 2 | Dr.C.Padmaja | Asst.Prof. | Ph.D. | Wireless and Mobile Communication |
| 3 | Mr.Y.RakeshKumar | Asst.Prof. | M.Tech(Ph.D.) | Image Processing |
| 4 | Mr.P.Satyanarayana Goud | Asst.Prof. | M.Tech(Ph. D.) | Signaland Image Processing |
| 5 | Mr.L.Nagaraju | Asst.Prof. | M.Tech(Ph. D.) | Antennaarray signal
processing |
Gallery:
Facilities
The Centreof Excellence inSignal Processing and Machine Learning had the following software and hardware kits. Thefacilities are available for all faculty and students who would like to participate in Signal Processing and Machine Learning.
R&D activities:
Software’s:
Anaconda, Python, Tensor flow, Numpy, Scikit-Image, Librosa, Scipy, PyTorch, Jupyter +Notebook, MATLAB.
Hardware Kits
| S. No | Name | Quantity |
| 1 | Zoom H4N Handy Portable Digital Recorder, Finger print Recognition and Logitech webcam | 1 |
| 2 | Zed Zynq 7000-ARM/FPGA SOC development board | 2 |
Funded research projects carried out in Centre of Excellence in Signal Processing and Machine Learning
| S. No | Title of theProject | FundingAgency | SanctionedAmount in Lakhs | FacultyAssociated |
|
NIL |
||||
Faculty as Resource Persons
| S. No | Nameoftheprogram | LectureTopic | NameoftheFaculty | Duration | Venue | Organizedby |
| 1 | AICTE-ISTE Sponsored Induction/Refresher Program on “OPTIMIZATION in
COMMUNICATION ENGINEERING” December 22-29, 2021 |
“Implementation using Excel Solver and MATLAB Optimization Toolbox”
(11.45AM-1.15PM) On 27-12-2021 Monday) |
Dr. C. Padmaja | 1.30 hrs | GNITS | AICTE-ISTE |
| 2 | AICTE-ISTE Sponsored Induction/Refresher Program on “Free and Open-Source ICT Tools for Effective Teaching-Learning and Research” | “TinkerCAD Simulator”
January 03– 08,2022 through online mode. from 9:30 to 11:30 AM |
Dr. C. Padmaja | 2 hrs | GNITS | AICTE-ISTE |
| 3 | Faculty Development Program on, “IOT Using Arduino Hardware” organized by SWEC, Hyderabad, 19/07/2021 – 24/07/2021 | “Project Development using Virtual Arduino” on 22/07/2021from
10AM-12PM |
Dr. C. Padmaja | 1.30 hrs | SWEC | SWEC, Hyderabad |
| 4 |
Faculty as Reviewers and Editorial board members
| S.No. | Name of thefaculty | Nature ofContribution | Details of associated Organization /Journal/ Conferenceetc. |
| 1 | Dr. C. Padmaja | Reviewer for IEEE Sensor Council U.P. Chapter | Motilal Nehru National Institute of Technology Allahabad Prayagraj, India organized by MAC2023 24th -26th March 2023 |
| 2 | Dr. C. Padmaja | Reviewer for 1st IEEE MTT / AP Society Bangalore JT Chapter MAPCON | IEEE MTT / AP Society Bangalore JT Chapter MAPCON December
12th -15th 2022 |
| 3 | Y Rakesh Kumar | Technical paper Reviewer | IEEE Access, IET Image Processing, Journal of Intelligent Systems, Journal of Scientific Research
|
| 4 | Dr. P. Chandrasekhar | Technical paper Reviewer | Reviewed the revision of JASA-06243R1, “Long-term scalogram integrated with an iterative data augmentation scheme for acoustic scene classification,” The Journal of the Acoustical Society of America, Apr 30, 2021.
|
Faculty Awards and Recognitions
| S.No. | Name of theFaculty | Designation | Detailsof theawardandrecognition |
| 1 | Dr. C. Padmaja | Assistant Professor | Outstanding Woman Researcher in Wireless Communication in 7th Venus International Women Awards (VIWA 2022) |
| 2 | Dr. C. Padmaja | Assistant Professor | DR. SARVEPALLI RADHAKRISHNAN Best Teacher Award on September 5th 2021 |
| 3 | Y Rakesh Kumar | Assistant Professor | IEAE Young Achiever Award 2018 for best paper publication |
| 4 | Y Rakesh Kumar | Assistant Professor | Best Senior Faculty Award 2021 by Novel Research Academy, Puducherry, India. |
| 5 | Y Rakesh Kumar | Assistant Professor | IETE 2nd Best Faculty Coordinator Award 2022 by IETE Hyderabad center. |
Details of Faculty Professional Body Memberships
| S. No | Name of the Faculty | MembershipNo. | |||||
| IEEE | ISTE | IETE | IEI | InternetSociety | OTHERS | ||
| 1 | Dr. C. Padmaja | 96774681 | LM 123287 | F-502931 | |||
| 2 | Y Rakesh Kumar | F502138 | INSC20180351 | ||||
| 3 | Dr. P. Chandrasekhar | -F503898 | |||||
| 4 | Satyanarayana Goud | LM95662 | |||||
| 5 | |||||||
Industry interactions
Listof MOUs with Signal Processing and Machine Learningindustries
| S.No. | Nameoftheindustry | Impact |
| 1 | PVR Tech Ltd, Hyderabad | Projects done by the students based on AI algorithms |
List of Industry personals associated
Guest lectures delivered by Industry experts during last 3 Years
| S. No | Name of the industry personal | Industry associated | Title | Date |
| 1 | N. Venkatesh
|
Senior Director, Silicon Labs, Hyderabad | Next Gen Camera and Imaging Systems | 15-12-2023
(Friday) |
| 2 | Dr. V.P.S. Naidu | Senior Principal Scientist CSIR, NAL- Bangalore | Fundamentals of Image Fusion and Preprocessing Techniques | 11-12-2023
(Monday) |
| 3 | Amol Kodag | Leader for the MEIC CVG Portfolio | Connected Care: The Future of Better Health | 03-02-2021 |
| 4 | Dr. Anil Kumar, Scientist
|
Cultivation & crop management of Paddy straw Mushroom
ICAR-DIRECTORATE OF MUSHROOM RESEARCH, |
Mushroom Cultivation and Mushroom Disease Detection | 9/11/2020 |
| 5 | Dr. MPrameela | AG university, Rajendra Nagar, Hyderabad |
Smart Technology based Mushroom Cultivation
|
17/9/221 |
Internships Opportunities in Signal Processing and Machine Learning related industries
| S.No | NameoftheIndustry | Nameof the Student&RollNo |
| NIL | ||
AcademicprojectscarriedoutbyStudentProjects during2023-24
| S.No. | Name of student | Faculty | Title | Year |
| 1 | C Bhavitha Reddy, Marru Hamsika, K Sri Radha Madhavi, Gummalla Sindhuja | Tulasi sowjanya | AI based system for rotten fruit
classification and segregation |
2023-24 |
| 2 | Bashetty Shravani, Gali Jayanthi, Nandini Kothagolla, Tadiparthi Vaishnavi | Dr C.Padmaja | Fruit Classification using Tensorflow and Deployment on to Maix bit | 2023-24 |
Outcomes:
- Signal Processing and machine learning is much more focused on speech, image, video, visual data, or any other types of data and aims to identify and interpret appropriate sources of information related to real life scenarios.
- Reflect on the relevance of current and future Signal Processing and machine learning applications.
- Papers and conferences will be published, and projects will be implemented.
Papers published/communicated.
| S. No | TitleofthePaper | Name of theConference/Journal | ConferenceDates | Status of thepaper(Submiited/Accepted/Published) |
| 1. | Diagnosis of Brain Disease through Deep Learning Approaches | NeuroQuantology
Volume 20 Issue 10 Page 1622-1626 |
August 2022 | Published.
ISSN: 1303-5150 Doi: 10.14704/nq.2022.20.10.NQ55145 |
| 2 | Night Vision Thermal sensor based Animal Movement Observation using CNN and YOLO v3 | International Journal of Advances in Computer Science and Technology | June 2023 | Published |
| 3 | Mushroom Decay Detection using Deep Learning | International Journal of Emerging Trends in Engineering Research | Dec. 2023 | Published |
| 4 | CNN Based Rat Detection using Thermal Sensor
|
International Journal of Emerging Trends in Engineering Research | Dec. 2023 | Published |
| 5 | Dragon Fruit Stem Disease Detection Using Image Processing |
Intelligent Computing and Communication, Advances in Intelligent Systems and Computing |
2023 | Published |
| 6 | Comparative Analysis of Image Segmentation methods for mushroom Disease Detection | Soft computing and signal processing | 2023 | Published |
| 7 | Late fusion framework for Acoustic Scene Classification using LPCC, SCMC, and log-Mel band energies with Deep Neural Networks | Applied Acoustics | 2021 | Published |
Any other Information like News Paper clippings: NIL