Syed Zaheeruddin

@kitsw.ac.in

Assistant Professor, ECE Dept
kakatiya Institute of Technology and Science, Warangal.

Syed Zaheeruddin


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https://researchid.co/sdzaheeruddin
14

Scopus Publications

110

Scholar Citations

5

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Advanced Multi-Scale Enhanced U-Net for Efficient Land Cover Classification of Remote Sensing Images
    Syed Zaheeruddin, K. Suganthi
    International Journal of Advanced Computer Science and Applications, 2025
    For monitoring the environment, building cities, assessing crops, and studying the climate, it is very important to be able to accurately classify land cover from remote sensing images. Deep learning has made semantic segmentation work much better, especially with encoder-decoder designs like U-Net. Still, ordinary U-Net models have trouble capturing multi-scale contextual relationships, distinguishing narrow borders, and successfully emphasizing traits that are distinctive to an area. This work presents an Advanced Multi-Scale Enhanced U-Net (AMSE-U-Net) to address these difficulties. The AMSE-U-Net combines (i) multi-scale feature extraction, (ii) squeeze-and-excitation channel attention, and (iii) attention-gated skip connections. The model improves learning of both local and global features while getting rid of background noise that isn’t useful. Tests done on common remote sensing datasets show big improvements in Intersection over Union (IoU), pixel precision, and boundary delineation when compared to standard U-Net and similar models. The suggested AMSE-U-Net works better for generalization with only a little amount of extra processing power, making it good for monitoring land cover and the environment.
  • Crop and Weed Semantic Segmentation using a Fuzzy Transform based Active Contour Model
    Zaheeruddin Syed, K. Suganthi
    International Conference on Innovative Data Communication Technologies and Application Icidca 2023 Proceedings, 2023
    The idea of semantic segmentation is crucial in many different fields, Including robotic vision, medicine, and manv others. Weeds are one of the main factors that could reduce crop productivity, thus it is essential to understand how crucial semantic segmentation is in the agricultural industry in segmenting crops from weed. Images are usually taken in a variety of climatic environments. often making them with low contrast. Using a fuzzy transform, which improves Image quality reasonably and will able to brinz out shapes or areas of interest within an image. To the resultant image enhancement using fuzzy transform, the study applies an active contour model which with the heln of the level set method identifies the boundaries and objects which were hidden due to low contrast. The propossed method when applied in the sezmentation of crop and weed delivers promising results. The outcomes of this strategy demonstrate its effectiveness.
  • Image Segmentation using Hybrid Relay Level Sets
    Zaheeruddin Syed, K. Suganthi
    Icsccc 2023 3rd International Conference on Secure Cyber Computing and Communications, 2023
    This research article offers a fast and efficient method of image segmentation using hybrid relay level sets. This automata model of level sets is achieved by the creating subregions with accordance to that of the previous subregion's boundaries. The contour evolves to the desired object by continues small shifts in contour until the level set function is stabilized with ensured full segmentation. This approach has the advantage of detecting more boundaries without interaction to outside world and without specifying number of relays for final overall segmentation. This approach of image segmentation outperforms traditional level set methods in terms of its relay fashion of contour evolution.
  • Fuzzified Contrast Enhancement and Segmentation For Nearly Invisible Images
    Zaheeruddin Syed, Kanneboina Siddhartha, Thota Rahul, Aragonda Sneha, Ellandala Jhansi, et al.
    Icsccc 2023 3rd International Conference on Secure Cyber Computing and Communications, 2023
    Any computer vision application must first improve a picture before continuing to process it color details losses during the enhancement process is a prevalent issue with most current techniques when applied to photographs that are essentially unnoticeable the qualitatively undetectable image should be improved while maintaining its freshness and coloring. Histogram equalization, a traditional approach of contrast enhancement, resulting in more than enhancement of something like the picture, particularly one with poorer resolution. The objective of this research is to develop an innovative fuzzy inference system capable of enhancing the contrast of low-resolution photos while simultaneously addressing any existing limitations, existing techniques and segmenting the tumor in MRI images. The outcomes from the two methods are contrasted. Throughout this research, the technique results in a very tiny change in intensity value while maintaining the image's information about color and brightness. The method enhances striking contrast while preserving naturalness without introducing any artefacts. Active contour processing on these photos produces extremely accurate segmentation results. Mainly this is used to detect the tumor in MRI images with some basic morphological operations.
  • Image Contrast Enhancement by Homomorphic Filtering based Parametric Fuzzy Transform
    Syed Zaheeruddin, K. Suganthi
    Procedia Computer Science, 2019
  • IR based color image preprocessing using PCA with SVD equalization
    Narsimha Baddiri, B. Naveen Kumar Christu, B. Santhosh Kumar, Syed Zaheeruddin
    International Conference on Intelligent Systems Design and Applications Isda, 2012
    In this paper we presented a color image enhancement model to overcome the drawbacks associated with illumination-reflectance model of color image enhancement. In this work a new color image enhancement technique based on the Principal Component Analysis (PCA) and singular value decomposition is proposed and comparative analysis is made with IR based model using discrete wavelet transform (DWT) & SVD and Retinex model. The real color image is transformed from RGB to HSV space which is an orthonormal transform between achromatic and chromatic components. The chromatic component is decomposed in to illumination and reflectance using Homomorphic filtering and the reflectance image is accounted for the variation in brightness and is decomposed into four Principal components using (PCA) which involves decomposition of an image into feature based low frequency and high frequency sub bands. Estimates of singular value matrix are carried on low frequency which accounts for contrast of the image, and then modified reflectance is achieved from SVD equalized principal component. The experiment results reveal that the proposed method shows that the color images are enhanced with details preserved and `halos' restrained. To indicate the impact of enhancement of true color images quantitative measurements like discrete entropy, relative entropy and quality metrics are computed.
  • Particle Swarm Optimization clustering based Level Sets for image segmentation
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    2012 Annual IEEE India Conference Indicon 2012, 2012
    Particle Swarm Optimization (PSO) is population based stochastic algorithm to form clusters with the help of fitness functions. PSO clustering algorithm is widely used in pattern recognition methods such as image segmentation where PSO defines less number of clusters compared to conventional clustering approaches. Level Sets image segmentation aided with the clustering gives fast convergence towards the desired boundaries of the object to be segmented. Here in this paper a novel approach of image segmentation using PSO clustering applied to Level sets is been presented where PSO performs better than KFCM by generating more compact clusters and larger inter cluster separation. The proposed method is successfully implemented on the images and results obtained show the effectiveness of the approach.
  • Segmentation of oil spill images with illumination-reflectance based adaptive level set model
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012
    This paper presents a novel method for segmenting the oil spill regions in the SAR satellite images taken in broad daylight using illumination-reflectance based level set model. These images of oil spills taken in broad daylight appear as a blend of dark areas with scintillations of glitter due to the illumination and reflectance components present. Most of the dark areas in the SAR images are the areas indicating oil spills because the oil dampens the capillary waves on the sea surface. The presence of the glitter induces speckle in SAR images. This does not only reduces the interpreter's ability to resolve fine detail, but also makes automatic segmentation of such images difficult. Segmentation of such images using conventional level set methods makes the process cumbersome and may lead to improper results. The accuracy of segmentation greatly depends on the amount of the illumination and reflectance (IR) components present in the images. To perform segmentation of such images we propose an adaptive level set evolution process based on the IR components in them. This can be achieved by combining a new signed pressure function which is derived from the amount illumination and reflectance present in the image. The IR components present in image are extracted by the process of homomorphic decomposition with the help of filters with specific cut off frequencies. This method is the first application successfully implemented on SAR images and the results are found to be superior when compared with earlier techniques. Comparative analysis is made with the conventional region based level sets in terms of accuracy of segmentation for complex images.
  • Biomedical image segmentation using spatial kernel fuzzy C-means based level set formulation
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    Journal of Medical Imaging and Health Informatics, 2012
  • Robust level set image segmentation based on modified fuzzy clustering
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    2011 International Conference on Multimedia Signal Processing and Communication Technologies Impact 2011, 2011
    Image segmentation by level set method greatly depends on appropriate initialization and optimal configuration of the contour controlling parameters. Here in this paper a novel, robust image segmentation based on fuzzy level set is been presented. Spatial fuzzy clustering is used for the initial segmentation and for considering controlling parameters of level set evolution. Level set algorithm is regularized with fuzzy clustering which facilitate in manipulations, leading to more robust image segmentation. The above process of segmentation showed a considerable improvement in the evolution of the level set function.
  • IR based level set evolution for segmentation of shadow images
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    2011 IEEE Recent Advances in Intelligent Computational Systems Raics 2011, 2011
  • Illumination-reflectance based novel approach for level set evolution
    Raghotham Reddy Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    IEEE International Conference on Electro Information Technology, 2011
  • Segmentation of shadow images using IR based adaptive Level set model
    G. Raghotham Reddy, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
    2011 International Conference on Signal Processing Communication Computing and Networking Technologies Icsccn 2011, 2011
  • Image segmentation using kernel fuzzy c-means clustering on level set method on noisy images
    G. Raghotham Reddy, K. Ramudu, Syed Zaheeruddin, R. Rameshwar Rao
    Iccsp 2011 2011 International Conference on Communications and Signal Processing, 2011

RECENT SCHOLAR PUBLICATIONS

  • Oil spill segmentation of noisy SAR images using domain adaptation based UNet
    S Zaheeruddin, K Suganthi
    Scientific Reports , 2026
    2026.0
  • Advanced Multi-Scale Enhanced U-Net for Efficient Land Cover Classification of Remote Sensing Images
    S Zaheeruddin, K Suganthi
    International Journal of Advanced Computer Science and Applications(IJACSA … , 2025
    2025.0
  • Fuzzified Contrast Enhancement and Segmentation For Nearly Invisible Images
    Z Syed, K Siddhartha, T Rahul, A Sneha, E Jhansi, K Suganthi
    2023 Third International Conference on Secure Cyber Computing and … , 2023
    2023.0
  • Image Segmentation using Hybrid Relay Level Sets
    Z Syed, K Suganthi
    2023 Third International Conference on Secure Cyber Computing and … , 2023
    2023.0
  • Crop and weed semantic segmentation using a fuzzy transform based active contour model
    Z Syed, K Suganthi
    2023 International Conference on Innovative Data Communication Technologies … , 2023
    2023.0
    Citations: 2
  • Noisy brain MR image segmentation using modified adaptively regularized kernel fuzzy c-means clustering algorithm
    KSMJ P. Yugander, K. Akshara, Syed Zaheeruddin
    https://link.springer.com/chapter/10.1007/978-981-19-7874-6_45 3 , 2022
    2022.0
  • A Combined Approach of Retinex & Spatial Kernel Fuzzy C-Means Clustering for Detection of Oil Spills in Satellite Imagery
    KS Syed Zaheeruddin
    International Conference on Sustainable Computing in Science and Technology … , 2019
    2019.0
  • A Combined Approach of Retinex & Spatial Kernel Fuzzy C-Means Clustering for Detection of Oil Spills in Satellite Imagery
    Z Syed, DK Suganthi
    Proceedings of International Conference on Sustainable Computing in Science … , 2019
    2019.0
    Citations: 1
  • Image contrast enhancement by homomorphic filtering based parametric fuzzy transform
    S Zaheeruddin, K Suganthi
    Procedia Computer Science 165, 166-172 , 2019
    2019.0
    Citations: 29
  • Particle swarm optimization clustering based level sets for image segmentation
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2012 Annual IEEE India Conference (INDICON), 1053-1056 , 2012
    2012.0
    Citations: 11
  • IR based color image preprocessing using PCA with SVD equalization
    N Baddiri, BNK Christu, BS Kumar, S Zaheeruddin
    2012 12th International Conference on Intelligent Systems Design and … , 2012
    2012.0
    Citations: 3
  • Segmentation of oil spill images with illumination-reflectance based adaptive level set model
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote … , 2012
    2012.0
    Citations: 38
  • Biomedical image segmentation using spatial kernel fuzzy c-means based level set formulation
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    Journal of Medical Imaging and Health Informatics 2 (2), 200-205 , 2012
    2012.0
    Citations: 5
  • Fpga implementation of vga controller
    Z Syed, M Shaik
    International Conference on Electronics and Communication Engineering, 46-51 , 2012
    2012.0
    Citations: 5
  • Robust level set image segmentation based on modified fuzzy clustering
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 International Conference on Multimedia, Signal Processing and … , 2011
    2011.0
  • IR based Level Set Evolution for segmentation of shadow images
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 IEEE Recent Advances in Intelligent Computational Systems, 885-889 , 2011
    2011.0
  • Segmentation of shadow images using IR based adaptive Level set model
    GR Reddy, S Zaheeruddin, N Baddiri, RR Rao
    2011 International Conference on Signal Processing, Communication, Computing … , 2011
    2011.0
  • Illumination-reflectance based novel approach for level set evolution
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY, 1-5 , 2011
    2011.0
  • Image segmentation using kernel fuzzy c-means clustering on level set method on noisy images
    GR Reddy, K Ramudu, S Zaheeruddin, RR Rao
    2011 International Conference on Communications and Signal Processing, 522-526 , 2011
    2011.0
    Citations: 16
  • Active Contours With New Signed Pressure Force Function For Echocardiographic Image Segmentation
    VL REDDY, S ZAHEERUDDIN

MOST CITED SCHOLAR PUBLICATIONS

  • Segmentation of oil spill images with illumination-reflectance based adaptive level set model
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote … , 2012
    2012.0
    Citations: 38
  • Image contrast enhancement by homomorphic filtering based parametric fuzzy transform
    S Zaheeruddin, K Suganthi
    Procedia Computer Science 165, 166-172 , 2019
    2019.0
    Citations: 29
  • Image segmentation using kernel fuzzy c-means clustering on level set method on noisy images
    GR Reddy, K Ramudu, S Zaheeruddin, RR Rao
    2011 International Conference on Communications and Signal Processing, 522-526 , 2011
    2011.0
    Citations: 16
  • Particle swarm optimization clustering based level sets for image segmentation
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2012 Annual IEEE India Conference (INDICON), 1053-1056 , 2012
    2012.0
    Citations: 11
  • Biomedical image segmentation using spatial kernel fuzzy c-means based level set formulation
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    Journal of Medical Imaging and Health Informatics 2 (2), 200-205 , 2012
    2012.0
    Citations: 5
  • Fpga implementation of vga controller
    Z Syed, M Shaik
    International Conference on Electronics and Communication Engineering, 46-51 , 2012
    2012.0
    Citations: 5
  • IR based color image preprocessing using PCA with SVD equalization
    N Baddiri, BNK Christu, BS Kumar, S Zaheeruddin
    2012 12th International Conference on Intelligent Systems Design and … , 2012
    2012.0
    Citations: 3
  • Crop and weed semantic segmentation using a fuzzy transform based active contour model
    Z Syed, K Suganthi
    2023 International Conference on Innovative Data Communication Technologies … , 2023
    2023.0
    Citations: 2
  • A Combined Approach of Retinex & Spatial Kernel Fuzzy C-Means Clustering for Detection of Oil Spills in Satellite Imagery
    Z Syed, DK Suganthi
    Proceedings of International Conference on Sustainable Computing in Science … , 2019
    2019.0
    Citations: 1
  • Oil spill segmentation of noisy SAR images using domain adaptation based UNet
    S Zaheeruddin, K Suganthi
    Scientific Reports , 2026
    2026.0
  • Advanced Multi-Scale Enhanced U-Net for Efficient Land Cover Classification of Remote Sensing Images
    S Zaheeruddin, K Suganthi
    International Journal of Advanced Computer Science and Applications(IJACSA … , 2025
    2025.0
  • Fuzzified Contrast Enhancement and Segmentation For Nearly Invisible Images
    Z Syed, K Siddhartha, T Rahul, A Sneha, E Jhansi, K Suganthi
    2023 Third International Conference on Secure Cyber Computing and … , 2023
    2023.0
  • Image Segmentation using Hybrid Relay Level Sets
    Z Syed, K Suganthi
    2023 Third International Conference on Secure Cyber Computing and … , 2023
    2023.0
  • Noisy brain MR image segmentation using modified adaptively regularized kernel fuzzy c-means clustering algorithm
    KSMJ P. Yugander, K. Akshara, Syed Zaheeruddin
    https://link.springer.com/chapter/10.1007/978-981-19-7874-6_45 3 , 2022
    2022.0
  • A Combined Approach of Retinex & Spatial Kernel Fuzzy C-Means Clustering for Detection of Oil Spills in Satellite Imagery
    KS Syed Zaheeruddin
    International Conference on Sustainable Computing in Science and Technology … , 2019
    2019.0
  • Robust level set image segmentation based on modified fuzzy clustering
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 International Conference on Multimedia, Signal Processing and … , 2011
    2011.0
  • IR based Level Set Evolution for segmentation of shadow images
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 IEEE Recent Advances in Intelligent Computational Systems, 885-889 , 2011
    2011.0
  • Segmentation of shadow images using IR based adaptive Level set model
    GR Reddy, S Zaheeruddin, N Baddiri, RR Rao
    2011 International Conference on Signal Processing, Communication, Computing … , 2011
    2011.0
  • Illumination-reflectance based novel approach for level set evolution
    RR Ganta, S Zaheeruddin, N Baddiri, RR Rao
    2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY, 1-5 , 2011
    2011.0
  • Active Contours With New Signed Pressure Force Function For Echocardiographic Image Segmentation
    VL REDDY, S ZAHEERUDDIN