Dr G Jagadeeswar Reddy

@mgit.ac.in

Professor Electronics and Communication Engineering
Mahatma Gandhi Institute of Technology

Dr G Jagadeeswar Reddy


                        Download Compact PDF  
https://researchid.co/jagsuni

EDUCATION

B.Tech, M.Tech, Ph.D

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Signal Processing, Electrical and Electronic Engineering, Multidisciplinary
12

Scopus Publications

Scopus Publications

  • Using social networking evidence to examine the impact of environmental factors on social Followings: An innovative Machine learning method
    SVN Murthy, P.S. Ramesh, Pydimarri Padmaja, Bechoo Lal, G.Jagadeeswar Reddy, Narender Chinthamu
    Entertainment Computing, 2024
  • A NOVEL TECHNIQUE PREDICTING THE RICE LEAF DISEASES USING CONVOLUTIONAL NEURAL NETWORK
    Arpn Journal of Engineering and Applied Sciences, 2024
    Various ailments affect rice, a staple crop in India, across different stages of its growth. Identification of these diseases manually poses a significant challenge, especially for farmers lacking in-depth knowledge. Recently, there's been promising advancement in deep learning research through automated picture identification systems employing Convolutional Neural Network (CNN) models. To tackle the scarcity of rice leaf disease image datasets, we developed a deep learning model using Transfer Learning on a limited dataset. Our approach leverages VGG-16 to train and evaluate the proposed CNN architecture, drawing from rice field and internet datasets. Impressively, the model achieves a 95 percent accuracy rate. Key terms in this study include Deep Learning, Convolutional Neural Network (CNN), fine-tuning, and rice leaf diseases.
  • AN ASYMMETRICAL PSI-SHAPED MULTIBAND ANTENNA FOR WIRELESS APPLICATIONS
    Penchala Reddy Sura, Padmaja Nimmagadda, Ch Jyotsna Rani, Tathababu Addepalli, Jagadeesh Babu K, B. Y. V. N. R. Swamy, A. L. Siridhara, G. Jagadeeswar Reddy
    Telecommunications and Radio Engineering English Translation of Elektrosvyaz and Radiotekhnika, 2024
    In this article, a low-profile multiband asymmetrical psi-shaped antenna for different wireless applications is presented and analyzed. This multiband antenna consists of an asymmetrical psi-shaped radiator considered on a single layer FR4 substrate with compact dimensions. The better impedance matching characteristics between the radiating element and the signal source are obtained by employing a slotted structure. The designed antenna operates at six different frequency bands of 1.8-2.03 GHz [GSM1800, personal communication systems (PCS)], 4.64-5.35 GHz [wireless local area network (WLAN)], 6.05-6.95 GHz (C-band), 7.92-8.59 GHz (military), 9.55-11.14 GHz [fixed satellite service (FSS)], and 11.57-12.29 GHz (DBS) while the S<sub>11 </sub>value is lower than -10 dB. The Ansoft HFSS 21 electromagnetic simulator is employed to optimize the antenna dimensions and study the antenna functionality at the six different frequency bands. The designed antenna exhibits higher gain at six frequency bands. The developed multiband antenna is prototyped, and test results are generated to validate its performance. The simulation results authenticate acceptable agreement with the measurement results. This antenna is a good choice for GSM1800, PCS, WLAN, C-band, FSS, and military defense applications.
  • A High Gain Circularly Polarized Dual Band Antenna Array Using Sequential Phase Rotation Technique for Wireless Applications
    Penchala Reddy Sura, G. Jagadeeswar Reddy, M. Mohammad Hayath Rajvee, Katta Anil Kumar
    Wireless Personal Communications, 2023
  • AUTOMATIC MEASUREMENT OF CARDIOTHORACIC RATIO IN CHEST X-RAY IMAGES WITH PROGAN-GENERATED DATASET
    Arpn Journal of Engineering and Applied Sciences, 2023
  • Classification of fingerprint images with the aid of morphological operation and AGNN classifier
    Subba Reddy Borra, G. Jagadeeswar Reddy, E. Sreenivasa Reddy
    Applied Computing and Informatics, 2018
    The uniqueness, public recognition, firmness, and their least jeopardy of fingerprints made an extensively and proficiently utilized personal authentication metrics. Fingerprint technology is a biometric method that is used to recognize persons on the basis of their physical traits. These physical forms comprise of ridges and valleys prevailing on the surface of fingertips. Fingerprint images are direction-oriented pattern fashioned using ridges and valleys. The reputation of the fingerprint image regulates the durability of a fingerprint authentication scheme. For enhancing the restrictions of prevailing fingerprint image augmentation approaches we have proposed an effectual method to pact with various fingerprint images. The proposed methodology alienated into three modules. Primarily, the fingerprint image is endangered to denoising procedure where Wave atom transform is used. Once this procedure is accomplished the image augmentation is achieved for improving the classification rate. The morphological operation is used in our proposed technique in order to augment the image. The morphological operators such as dilation and area opening are used here for improvement. Finally the ordering of fingerprint image is done. Adaptive Genetic Neural Network (AGNN) is used for classification of images efficiently.
  • An efficient fingerprint identification using neural network and BAT algorithm
    Subba Reddy Borra, G. Jagadeeswar Reddy, E. Sreenivasa Reddy
    International Journal of Electrical and Computer Engineering, 2018
    The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor.
  • A broad survey on fingerprint recognition systems
    Subba Reddy Borra, G. Jagadeeswar Reddy, E. Sreenivasa Reddy
    Proceedings of the 2016 IEEE International Conference on Wireless Communications Signal Processing and Networking Wispnet 2016, 2016
    Fingerprints are extensively and effectively utilized for proof of identity in recent years. Mostly because of their originality, stability through life, a uniqueness among the people, public acceptance and their least risk of invasion. Fingerprint technology, which is a bio-metric system, is utilized to classify an individual based on their physical qualities. Fingerprint matching is the trendiest biometric technique utilized to provide authentication. At first, fingerprint identification mechanism scans for an unprocessed image, executes pre-processing and after that features of those images are defined as vectors and are protected in databases of fingerprint as image records. In this paper, a broad study on different features of fingerprint recognition systems are explained. Here we have presented broad categories of fingerprint patterns and consequently minute based method. Fingerprint ridges named as minutiae are capable of confine invariant and discriminating information exist in the database of fingerprint images. The different approaches that are based on Pattern recognition, wavelet and wave atom, are studied. Wave atom is the one of new geometric multiscale-multidirectional transform that is suitable for the representation of the fingerprint structures. The challenges and problems regarding fingerprint recognition systems and fingerprint orientation map using wave atom transform are reviewed analytically. So, to obtain higher accuracy it is very much necessary to utilize higher quality noise free fingerprint image as an input. Additionally, we have studied and presented different fingerprint image improvement technology in this paper.
  • An Efficient Fingerprint Enhancement Technique Using Wave Atom Transform and MCS Algorithm
    Subba Reddy Borra, G. Jagadeeswar Reddy, E. Sreenivasa Reddy
    Procedia Computer Science, 2016
    Fingerprints are widely and successfully used for personal identification. This is mainly due to their individuality, stability through life, uniqueness among people, public acceptance and their minimum risk of intrusion. Fingerprint technology is a biometric technique utilized to identify persons based on their physical traits. The physical patterns of this technique consist of ridges and valleys that exist on the surface of fingertips. Fingerprint images are direction-oriented patterns formed by ridges and valleys. The eminence of the fingerprint image is determined by the sturdiness of a fingerprint authentication system. In order to improve the limitations of existing fingerprint image enhancement methods an efficient technique is proposed to deal with low quality fingerprint images. The proposed methodology can be divided into three modules. In the first module, the fingerprint image is subjected to denoising process where Wave atom transform is utilized. After the completion of this process the image enhancement is performed with the help of optimization algorithm. In our enhancement approach, a Modified Cuckoo Search (MCS) algorithm is used as an optimizer. This helps to look for the best gray level distribution that maximizes the objective function.
  • Cognitive radio implementation with GRC
    Global Journal of Pure and Applied Mathematics, 2015
  • Lossy compression and curvelet thresholding for image denoising
    G. Jagadeeswar Reddy, T. Jaya Chandra Prasad, M.N. Giri Prasad
    International Journal of Information and Communication Technology, 2009
  • Lossy compression and curvelet thresholding for image denoising
    G. Jagadeeswar Reddy, T. Jaya Chandra Prasad, M.N. GiriPrasad
    2008 International Conference on Electronic Design Iced 2008, 2008