Implementation of Lane Tracking and Obstacle Avoidance algorithm on Jetbot 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Clothing Segmentation using HSV Features and Morphological Algorithms Bhupendra Fataniya, Diya Shah, Roshni Jariwala Proceedings of the 7th International Conference on Innovative Data Communication Technologies and Application Icidca 2025, 2025 This paper presents an automatic clothing segmentation method in images using MATLAB-based image processing techniques. the implementation utilized techniques such as HSV color space conversion, morphological operations, edge detection, thresholding, and binary masking, to isolate clothing regions from the background. The system was evaluated on a dataset of 50 images, comparing the outputs with manually annotated ground truth masks (via CVAT). Metrics such as Intersection over Union (IoU), Dice coefficient, Precision, Recall, Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR) were calculated and results were inferred from the same. The method achieved a mean IoU of 0.6203, Dice score of 0.7342, Precision of 0.9276, Recall of 0.6597, MSE of 0.1058, and PSNR of 10.96 dB, demonstrating reliable segmentation accuracy in clean-background scenarios. However, performance drops for occlusions, overlapping garments, and dark-colored clothes due to the limitations of basic image processing techniques, suggesting that future improvements could involve deep learning approaches, such as Convolutional Neural Networks (CNNs), to enhance segmentation under these challenging conditions.
Real-Time Object Detection in Microscopic Image of Indian Herbal Plants using YOLOv5 on Jetson Nano Yash Jha, Harsh Prajapati, Bhupendra Fataniya Proceedings of the 2022 International Conference on Connected Systems and Intelligence Csi 2022, 2022 Object detection has been evolving greatly in recent years and the advancements in hardware and software technologies have made it possible to perform object detection with ease. Due to the enhanced capabilities of the modern processors and Graphics Processing Unit (GPU) of doing an exponentially complex and extensive number of iterations in very less time. Real-time object detection has become highly popular and the center of attention in recent years because most of the hardware owned by common users is powerful enough to compute that which unlocks whole new possibilities for implementing real-time object detection in numerous applications in various domains. Real-time herbal plant detection is one such topic that has many applications in the field of ayurvedic medicines and many other pharmaceutical applications that can be used to spike the efficiency in identifying these herbal plants that can be used as a precaution and even as a cure for numerous health problems. There are many existing algorithms for real-time detection, but the evolution of new Artificial Neural Network (ANN) and Machine Learning (ML) techniques unlocks new ways to implement recent and advanced algorithms to apply for real-time detection of such powdered microscopic images to achieve better performance in various aspects compared to already existing methods. Our model is trained for detecting three types of microscopic herbal plants.
Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network Rohan Malhotra, Hemang Patel, Bhupendra D. Fataniya Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021 With the rising of the new pandemic, problems to detect the presence of Covid-19 also emerged. To track the infections, RT-PCR and rapid testing are followed in the current situation which is time-consuming and could be an important time for severe patients. To decrease the amount of time for COVID-19 prediction, Chest X-rays could play an important role in determining the result. So by using Chest X-rays with Artificial Intelligence, the COVID-19 disease can be detected in a lesser amount of time under the guidance of the specialist. For this, the Deep Learning techniques like Convolutional Neural Networks (CNN) have been proved quite successful for image recognition and classification. In this experiment, Covid-19 was detected with the help of ResNet architecture whose accuracy increases while going into deeper layers by using skip connections. ResNet is a pre-trained model on the ImageNet database. During the experiment, ResNet18 architecture was used because it has the least number of layers as compared to other CNN architectures and so, for determining the best accuracy obtained with lesser computations. Methods like k-fold cross-validation, confusion matrices, etc were used in obtaining the accuracy of around 89% for COVID-19 prediction. Hence, CNN could be a useful tool for the prediction of COVID-19 and saving time for both patients and doctors for further treatment.
Implementation of iot based waste segregation and collection system Bhupendra Fataniya, Aayush Sood, Deepti Poddar, Dhaval Shah International Journal of Electronics and Telecommunications, 2019 Waste management is a challenging problem for most of the countries. The current waste segregation and the collection method are not efficient and cost-effective. In this paper, a prototype is presented for smart waste management. It is also capable of waste segregation at the ground level and providing real-time data to the administrator. Impact and cost analysis of the deployment of smartbin is also presented considering one ward of Ahmedabad Municipal Corporation. It is clear from that deployment of this smartbin will save about 40% of the current expenditure for that ward.
Clothing Segmentation using HSV Features and Morphological Algorithms B Fataniya, D Shah, R Jariwala 2025 7th International Conference on Innovative Data Communication … , 2025 2025
Impact of Hardware Trojan on Cache Replacement Policy D Shah, SD Anjaria, B Fataniya International Conference on ICT for Sustainable Development, 272-281 , 2025 2025 Citations: 1
SD-YOLOv5: Implementation of Real-Time Staircase Detection on Jetson Nano Board B Fataniya, A Mecwan, D Shah, M Chauhan, J Dave SN Computer Science 6 (4), 340 , 2025 2025 Citations: 3
Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model R Patel, N Patel, B Fataniya, D Shah SN Computer Science 5 (4), 350 , 2024 2024 Citations: 2
Real-time object detection in microscopic image of Indian herbal plants using YOLOv5 on Jetson Nano Y Jha, H Prajapati, B Fataniya 2022 International Conference on Connected Systems & Intelligence (CSI), 1-8 , 2022 2022 Citations: 6
Microscopic image analysis for herbal plant classification BD Fataniya, T Zaveri International Journal of Image Mining 4 (1), 1-23 , 2021 2021
Software tools for global navigation satellite system R Soni, S Gajjar, M Upadhyay, B Fataniya International Conference on Information and Communication Technology for … , 2020 2020 Citations: 4
MICROSCOPIC IMAGE ANALYSIS FOR HERBAL PLANT CLASSIFICATION T ZAVERI, BD FATANIYA INTERNATIONAL JOURNAL 1 (1), 1 , 2020 2020
Implementation of IoT based waste segregation and collection system B Fataniya, A Sood, D Poddar, D Shah International Journal of Electronics and Telecommunications 65 , 2019 2019 Citations: 25
Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning R Marwaha, B Fataniya 2018 Fifth International Conference on Parallel, Distributed and Grid … , 2018 2018 Citations: 8
Microscopic Image Based Classification Algorithms for few Herbal Plants Identification using Machine Learning Approaches BM Fataniya Institute of Technology, Nirma University Ahmedabad , 2018 2018 Citations: 1
Classification of microscopic image of herbal plants from its powder using speeded-up robust features B Fataniya, T Zaveri, S Acharya Journal of Advanced Microscopy Research 13 (3), 326-332 , 2018 2018 Citations: 4
Herbal Plant Classification Using Rotational and Scale Invariant Shape Based Features B Fataniya, T Zaveri, S Acharya Sensor Letters 16 (8), 624-631 , 2018 2018
Automatic Image Segmentation Algorithm for Microscopic Images of Liquorice and Rhubarb S Vyas, B Fataniya, T Zaveri, S Acharya Proceedings of the Third International Symposium on Computer Vision and the … , 2016 2016 Citations: 2
Edge Detection of Microscopic Image B Fataniya, M Kar, G Joshi, DT Zaveri, DS Acharya International Journal of Electronics and Communication Engineering … , 2016 2016 Citations: 5
Implementation of Edge Detection Algorithm on FPGA using Hardware Software Co-Simulation DS Bhupendra Fataniya, Akash Mecwan Journal of VLSI Design Tools & Technology 6 (1), 55-61 , 2016 2016 Citations: 1
Innovations in evaluation: An integral part of outcome based education AI Mecwan, DG Shah, BD Fataniya 2015 5th Nirma University International Conference on Engineering (NUiCONE), 1-5 , 2015 2015 Citations: 8
Innovations in Evaluation: An Integral Part of Outcome Based Education DS Bhupendra Fataniya, Akash Mecwan NUiCONE'15 , 2015 2015
Automatic identification of licorice and rhubarb by microscopic image processing B Fataniya, M Joshi, U Modi, T Zaveri Procedia Computer Science 58, 723-730 , 2015 2015 Citations: 10
Microscopic Image Analysis Method for Identification of Indian Herbal Plants SA Bhupendra Fataniya, Prachi Patel, Tanish Zaveri International Conference on Devices, Circuits and Communications (ICDCCom … , 2014 2014 Citations: 13
MOST CITED SCHOLAR PUBLICATIONS
Implementation of IoT based waste segregation and collection system B Fataniya, A Sood, D Poddar, D Shah International Journal of Electronics and Telecommunications 65 , 2019 2019 Citations: 25
Microscopic Image Analysis Method for Identification of Indian Herbal Plants SA Bhupendra Fataniya, Prachi Patel, Tanish Zaveri International Conference on Devices, Circuits and Communications (ICDCCom … , 2014 2014 Citations: 13
Automatic identification of licorice and rhubarb by microscopic image processing B Fataniya, M Joshi, U Modi, T Zaveri Procedia Computer Science 58, 723-730 , 2015 2015 Citations: 10
Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning R Marwaha, B Fataniya 2018 Fifth International Conference on Parallel, Distributed and Grid … , 2018 2018 Citations: 8
Innovations in evaluation: An integral part of outcome based education AI Mecwan, DG Shah, BD Fataniya 2015 5th Nirma University International Conference on Engineering (NUiCONE), 1-5 , 2015 2015 Citations: 8
Real-time object detection in microscopic image of Indian herbal plants using YOLOv5 on Jetson Nano Y Jha, H Prajapati, B Fataniya 2022 International Conference on Connected Systems & Intelligence (CSI), 1-8 , 2022 2022 Citations: 6
Edge Detection of Microscopic Image B Fataniya, M Kar, G Joshi, DT Zaveri, DS Acharya International Journal of Electronics and Communication Engineering … , 2016 2016 Citations: 5
Software tools for global navigation satellite system R Soni, S Gajjar, M Upadhyay, B Fataniya International Conference on Information and Communication Technology for … , 2020 2020 Citations: 4
Classification of microscopic image of herbal plants from its powder using speeded-up robust features B Fataniya, T Zaveri, S Acharya Journal of Advanced Microscopy Research 13 (3), 326-332 , 2018 2018 Citations: 4
SD-YOLOv5: Implementation of Real-Time Staircase Detection on Jetson Nano Board B Fataniya, A Mecwan, D Shah, M Chauhan, J Dave SN Computer Science 6 (4), 340 , 2025 2025 Citations: 3
Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model R Patel, N Patel, B Fataniya, D Shah SN Computer Science 5 (4), 350 , 2024 2024 Citations: 2
Automatic Image Segmentation Algorithm for Microscopic Images of Liquorice and Rhubarb S Vyas, B Fataniya, T Zaveri, S Acharya Proceedings of the Third International Symposium on Computer Vision and the … , 2016 2016 Citations: 2
Impact of Hardware Trojan on Cache Replacement Policy D Shah, SD Anjaria, B Fataniya International Conference on ICT for Sustainable Development, 272-281 , 2025 2025 Citations: 1
Microscopic Image Based Classification Algorithms for few Herbal Plants Identification using Machine Learning Approaches BM Fataniya Institute of Technology, Nirma University Ahmedabad , 2018 2018 Citations: 1
Implementation of Edge Detection Algorithm on FPGA using Hardware Software Co-Simulation DS Bhupendra Fataniya, Akash Mecwan Journal of VLSI Design Tools & Technology 6 (1), 55-61 , 2016 2016 Citations: 1
A robust two-stage super-resolution algorithm P Chaudhary, B Fataniya 2012 Nirma University International Conference on Engineering (NUiCONE), 1-6 , 2012 2012 Citations: 1
Clothing Segmentation using HSV Features and Morphological Algorithms B Fataniya, D Shah, R Jariwala 2025 7th International Conference on Innovative Data Communication … , 2025 2025
Microscopic image analysis for herbal plant classification BD Fataniya, T Zaveri International Journal of Image Mining 4 (1), 1-23 , 2021 2021
MICROSCOPIC IMAGE ANALYSIS FOR HERBAL PLANT CLASSIFICATION T ZAVERI, BD FATANIYA INTERNATIONAL JOURNAL 1 (1), 1 , 2020 2020
Herbal Plant Classification Using Rotational and Scale Invariant Shape Based Features B Fataniya, T Zaveri, S Acharya Sensor Letters 16 (8), 624-631 , 2018 2018
