Papers by Dattatraya Jadhav
International Conference on Communication and Information Processing (ICCIP-2020) , 2020
Distinguishing shot boundaries and Gradual shot change happens to be critical research area in th... more Distinguishing shot boundaries and Gradual shot change happens to be critical research area in the field of video retrieval, summarization and segmentation. Identification of Video shot boundaries is generally a significant and first step for ordering, retrieval, video segmentation and event based video analysis and numerous other such aspects. There has been extraordinary research to improve the accuracy of SBD calculations. An advance research on this work is reported towards interpretable highlights of edges. In this paper, we projected an identification of video shot structure dependent on Convolutional Neural Systems (CNNs). The method proposed in this paper uses RAI Dataset with the CNN network with improved results than traditional practices. We have tested the proposed system on the TRECVID IACC.3 dataset and made use of Keras and TensorFlow algorithms. Segmentation of videos in to fragment which extract video shots and separate the video shot boundary. This sort of preprocessing strategy helps in improving both the speed and precision of the SBD calculation. In the next part shots are extracted through semantic mark which is produced during shot detection. The projected algorithm performs well when compared with Adaptive algorithm in term of recall, Precision and F1 measure. The data set consist of standard videos (Movie Gods of Egypt, Tennis Sports, Bulletin news, Traffic Video playback, Krishna's Carton).
International Journal of Advances in Engineering & Technology, May 2012. ©IJAET, 2012
A simple and efficient approach for the implementation of Optical Character Recognition is presen... more A simple and efficient approach for the implementation of Optical Character Recognition is presented by making use of six different image analysis phases followed by image detection via pre-processing and postprocessing. Also, the scanning of the document and recognizing individual characters from image irrespective of their position, size, and various font styles has been discussed. Although, it deals with the recognition of symbols from English language, which can easily be extended for large set of symbols especially other languages. All phases of analysis have been implemented in MATLAB.
Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org, 2020
Shot boundary detection is the fundamental step of video retrieval, summarization, and analysis. ... more Shot boundary detection is the fundamental step of video retrieval, summarization, and analysis. In our paper, bidirectional empirical mode decomposition (BEMD) is presented into the shot boundary detection method. Using this method, every frame present in videos is decomposed by BEMD into a series of Intrinsic Mode Function images and a residue image. The IMF image having the lowest frequency of each frame is cast-off and an auxiliary frame is composed back by the other IMF images and the residue image. By employing these substitute frames to compute variances of adjacent frames unwanted detections are avoided which may be caused by immediate illumination changes. Further to avoid unwanted detections caused due to object motions, we have also applied a region-based object tracking method. The results proposed in this paper demonstrate that the precision of detecting shot boundaries is significantly improved.
Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org, 2020
Detecting shot boundary and gradual shot change happens to the prominent research problem in the ... more Detecting shot boundary and gradual shot change happens to the prominent research problem in the field of video retrieval or indexing. Video shot boundary detection (SBD) is commonly an important and first step for indexing, and retrieval, video data, browsing, and content-based video analysis and many other such technologies. There have been great efforts put forward to enhance the precision of SBD algorithms. But many of these works are oriented towards signal and not towards interpretable features of frames. In our paper, we put forward a video shot boundary detection structure based on Convolutional Neural Networks (CNNs). Candidate segment selection is adopted which determines the locations of shot boundaries and removes most non-boundary frames. This kind of preprocessing method helps in improving both the speed and accuracy of the SBD algorithm. Later on, features of frames in a shot are synthesized and semantic labels for the shot are generated. This modular CNN network will be superior to the state-of-art methods on RAI Dataset with better than average real-time deduction speed even on just one mediocre GPU. Randomly generated transitions using selected shots from the TRECVID IACC.3 dataset will be employed under the training process. The proposed system achieved an average precision of 0.966, recall of 0.864 and F1 score of 0.912.
GIS SCIENCE JOURNAL, 2022
We introduce IoT based bridge monitoring system using GSM technology. As we know, aging and deter... more We introduce IoT based bridge monitoring system using GSM technology. As we know, aging and deterioration of transport infrastructure facilities are very important safety concerns, especially when the use of these structures is increasing. Wireless smart sensor networks are evolving nowadays, making remote monitoring applications cost-effective and feasible across a wide range of geographic areas. Data from various sensors are processed by a microcontroller and transmitted to a mobile telecommunication device via the GSM model for real-time monitoring of the bridge setup.
International Journal of Emerging Technology and Advanced Engineering , 2013
Air pollution has harmful effects that cause acid rain global warming. To reduce these effects ai... more Air pollution has harmful effects that cause acid rain global warming. To reduce these effects air pollution monitoring system is important. A low power wireless sensor network and control of inter-node data reception for use in the real time acquisition and communication of air pollutants such as SO2, CO, NO2 and NO etc. The main objective is achieved by interfacing various sensors to measure the common air pollutants. The measured data is displayed on the monitor using the graphical user interface (GUI). The data based server is attached to the pollution server for storing the pollutants level. Pollution server is interfaced to Google maps to display real time pollutants, pollutants level and locations in large areas.
International Journal for Research in Applied Science and Engineering Technology
Messungen der Ladung und der Fallgeschwindigkeit von Regentropfen auf einer tropischen Station
ICTACT Journal on Image and Video Processing, Nov 1, 2010
GIS SCIENCE JOURNAL, 2022
We introduce IoT based bridge monitoring system using GSM technology. As we know, aging and deter... more We introduce IoT based bridge monitoring system using GSM technology. As we know, aging and deterioration of transport infrastructure facilities are very important safety concerns, especially when the use of these structures is increasing. Wireless smart sensor networks are evolving nowadays, making remote monitoring applications cost-effective and feasible across a wide range of geographic areas. Data from various sensors are processed by a microcontroller and transmitted to a mobile telecommunication device via the GSM model for real-time monitoring of the bridge setup.
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2024
Brain tumors, whether benign or malignant, pose significant risks, especially in children and you... more Brain tumors, whether benign or malignant, pose significant risks, especially in children and young adults, impacting both life expectancy and quality of life. This review addresses the critical importance of early detection and treatment of brain tumors. With a focus on artificial intelligence, particularly object detection using the YOLOv8 model, the paper explores the potential for accurate and efficient brain tumor detection from magnetic resonance images (MRI). The YOLOv8 model is known for its real-time performance, efficiency, and high accuracy, making it a promising tool in the field of medical image analysis. The paper presents a method for brain cancer detection and localization, discusses experimental results, reviews the state-of-theart literature, and outlines future research directions.
This research introduces a groundbreaking approach to address the challenges of cost-efficient da... more This research introduces a groundbreaking approach to address the challenges of cost-efficient data communication in Wireless Sensor Networks (WSNs) through the development of a novel routing protocol named Cost-Efficient Enhanced Routing Protocol (CEERP). WSNs, characterized by resource-constrained sensor nodes and dynamic environmental conditions, necessitate innovative routing strategies to optimize energy consumption and enhance overall network performance. CEERP leverages a sophisticated methodology that integrates Energy Consumption Modeling, Adaptive Routing Decisions, alongside Optimization and Fine-Tuning. The Energy Consumption Modeling method systematically analyzes various factors influencing energy dynamics in sensor nodes, facilitating the creation of accurate mathematical models. These models inform CEERP's routing algorithm, enabling intelligent decisions based on predicted energy consumption patterns. The protocol adapts dynamically to real-time variations in network conditions, ensuring responsiveness to changing environmental factors. Implementation and Simulation validate CEERP's performance in diverse scenarios, while Optimization and Fine-Tuning fine-tune parameters for optimal efficiency. Security and reliability measures are integrated to safeguard data integrity. The research concludes with a comprehensive evaluation of CEERP's effectiveness, positioning it as a promising solution for achieving cost-efficient and reliable data communication in WSNs. The proposed methodology and CEERP contribute to the advancement of routing protocols for WSNs, offering a holistic and adaptive approach to address the unique challenges posed by resource-constrained environments.
Pattern Recognition and Image Analysis, Jul 1, 2017
Conventional gait recognition schemes has poor recognition accuracies in presence of covariates. ... more Conventional gait recognition schemes has poor recognition accuracies in presence of covariates. It is mainly due to ineffective and inefficient representation and discriminative feature extraction schemes. The paper presents new technique to extract discriminative features from masked gait energy image based on curvelet transform and PCANet. The binary gait silhouette video sequence obtained from pre-processing of video sequence is converted in to masked gait energy image and then direction and edge representation ability of fast discrete curvelet transform is employed. Nonlinear and non invertible, image space to feature space mapping scheme of PCANet is used to extract discriminative robust features. The suitability and effectiveness of newly proposed scheme is demonstrated by experimentation on standard publicly available benchmark USF HumanID database.
Adaptive Background Subtraction Models for Shot Detection
Springer eBooks, 2021
Preliminary observations with the new grating monochromator
Observations of Coronal Velocity Field Flash Spectrum and Shadow Bands during Solar Eclipse 1980
Bulletin of the Astronomical Society of India
A new polarimeter for emission corona
Bulletin of the Astronomical Society of India
Solar and Interplanetary Dynamics, 1980
Solar Flares in Boulder Active Region No. 2372 during April 7-13 1980
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Papers by Dattatraya Jadhav