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公开(公告)号：US20240420464A1
公开(公告)日：2024-12-19
申请号：US18742019
申请日：2024-06-13
Applicant: Tata Consultancy Services Limited
Inventor： Shruti Kunal KUNDE , Ravi Kumar SINGH , Chaman BANOLIA , Rekha SINGHAL , Balamuralidhar PURUSHOTHAMAN , Shailesh Shankar DESHPANDE
IPC: G06V20/10 , G06V10/26 , G06V10/762 , G06V10/764 , G06V10/766 , G06V10/77
Abstract: The disclosure addresses problems associated with a systematic integration of multi-modal data for effective training, and handling of large volume of data because of high resolution of the multiple modalities. Embodiments herein provide a method and a system for a distributed training of a multi-modal data fusion transformer. Herein, a distributed training approach called a Distributed Architecture for Fusion-Transformer Training Acceleration (DAFTA) is proposed for processing large multimodal remote sensing data. DAFTA is enabled to handle any combination of remote sensing modalities. Additionally, similarity of feature space is leveraged to optimize the training process and to achieve the training with reduced data set which is equivalent to a complete data set. The proposed approach provides a systematic and efficient method for managing large sensing data and enables accurate and timely insights for various applications.
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2.发明公开公开(公告)号：US20240185598A1
公开(公告)日：2024-06-06
申请号：US18385581
申请日：2023-10-31
Applicant: Tata Consultancy Services Limited
Inventor： Shailesh Shankar DESHPANDE , Jayantrao Mohite , Mariappan Sakkan , Suryakant Ashok Sawant , Srinivasu Pappula , Balamuralidhar Purushothaman
IPC: G06V20/10 , G06Q30/018 , G06Q50/02 , G06V10/764 , G06V10/766 , G06V10/774 , G06V20/50
CPC classification number: G06V20/188 , G06Q30/018 , G06Q50/02 , G06V10/764 , G06V10/766 , G06V10/774 , G06V20/194 , G06V20/50
Abstract: This disclosure relates generally to method and system to calculate net carbon sequestration for agriculture using remote sensing data. Climate change is one of the factor in sustainable development on the earth and has sparked numerous initiatives to reduce earth's carbon footprint. The disclosed method processes remote sensing data comprising one or more input images indicating one or more characteristics of at least one agriculture crop of a geographical region. The method calculates a carbon footprint value of at least one agriculture crop by obtaining a plurality of carbon values associated with the geographical region. A net carbon flux of least one agriculture crop is calculated based on the carbon footprint value, a data maturity index, and a difficulty level. The method enables growers and carbon credit purchasers to correctly determine the carbon footprint of a geographical region to accurately predict the reduction of greenhouse gas emissions reducing environmental degradation.
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公开(公告)号：US20230196099A1
公开(公告)日：2023-06-22
申请号：US17970975
申请日：2022-10-21
Applicant: Tata Consultancy Services Limited
CPC classification number: G06N3/08 , G06T5/006 , G06T7/0002 , G06T2207/10032 , G06T2207/20081
Abstract: The embodiments of present disclosure herein address problem of urban metabolism with respect to water demand and carbon dioxide emissions, the discussion is based on the reported data by the urban areas. The embodiments herein provide a method and system for estimating urban metabolism based on remotely sensed data. The system is configured to develop a model for identifying correct features from image or proxy features from image and then develop/use relation between the image feature or proxy feature from the image with the urban metabolic parameter. Further, the system develops an urban growth model which predicts spatial extent of the given proxy features. The urban growth scenario for each such conditions is different. By changing conditions of the model, different growth scenarios are played out. For each scenario, at least one urban metabolic parameter is predicted by taking output of the urban growth predictor.
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公开(公告)号：US20220319144A1
公开(公告)日：2022-10-06
申请号：US17513011
申请日：2021-10-28
Applicant: Tata Consultancy Services Limited
IPC: G06V10/24 , G06V10/44 , G06V10/774 , G06V10/25 , G06T7/11
Abstract: State of art techniques performing image labeling of remotely sensed data are computation intensive, consume time and resources. A method and system for efficient retrieval of a target in an image in a collection of remotely sensed data is disclosed. Image scanning is performed efficiently, wherein only a small percentage of pixels from the entire image are scanned to identify the target. One or more samples are intelligently identified based on sample selection criteria and are scanned for detecting presence of the target based on cumulative evidence score Plurality of sampling approaches comprising active sampling, distributed sampling and hybrid sampling are disclosed that either detect and localize the target or perform image labeling indicating only presence of the target.
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公开(公告)号：US20180268247A1
公开(公告)日：2018-09-20
申请号：US15869311
申请日：2018-01-12
Applicant: Tata Consultancy Services Limited
Inventor： Jayavardhana Rama GUBBI LAKSHMINARASIMHA , Karthikeyan VAIAPURY , Mariswamy Girish CHANDRA , Balamuralidhar PURUSHOTHAMAN , Shailesh Shankar DESHPANDE
CPC classification number: G06K9/4671 , G06K9/0063 , G06K9/00791 , G06K9/3241 , G06K9/4623 , G06K9/6215 , G06K2009/3291 , G06K2009/6213
Abstract: A system and method for identifying real time change in a scene of an unknown environment using an unmanned vehicle. In the context of unmanned vehicle navigation, it is critical to calculate the saliency map in real time and employ them in scene understanding. This will reduce the search space and ensure that the process is quicker. A domain specific ontology is created and a saliency model is developed. The saliency model detects key domain specific regions of interest in two consecutive images. The regions of interest is used for registration and change detection. The system is detecting the change by using visual saliency as an abstract feature that is developed in the environment. Probability of change is derived using the salient maps of the two images.
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Patent Agency Ranking
公开(公告)号：US20240095956A1
公开(公告)日：2024-03-21
申请号：US18233352
申请日：2023-08-14
Applicant: Tata Consultancy Services Limited
CPC classification number: G06T7/80 , G06V20/13 , G06V20/176 , G06V20/188 , G06T2200/28 , G06T2207/10032 , G06T2207/20036 , G06T2207/20076 , G06T2207/30184 , G06T2207/30188
Abstract: Embodiments herein provide a method and system for a vicarious calibration of optical data from satellite sensors for urban scene flat fields. Identifying test sites automatically in the urban scene helps in vicarious calibration or on-board calibration of the hyperspectral/multispectral image. An internal average relative reflectance is calculated to get a relative reflectance of the image. Band ratios for various pixels is determined to assess flatness of the spectrum. Flat field candidates are identified from the various pixels having average band ratio nearing zero and a morphological technique is applied to determine a flat field. Finally, the image is calibrated vicariously based on the determined flat field as a test site. The on-board calibration of the remote sensing image may lead to a faster way to get the reflectance image of the scene, with the help of the calibration constants.
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公开(公告)号：US20170091641A1
公开(公告)日：2017-03-30
申请号：US15271913
申请日：2016-09-21
Applicant: Tata Consultancy Services Limited
Abstract: The present disclosure provides a method and a system for optimizing Hidden Markov Model based land change prediction. Firstly, remotely sensed data is pre-processed and classified into a plurality of land use land cover classes (LULC). Then socio-economic driver variables data for a pre-defined interval of time are provided from a database. A Hidden Markov Model (HMM) is defined with LULC as hidden states and socio-economic driver variables data as observations and trained for generating a HMM state transition probability matrix. Again the defined HMM is trained by taking input data from scenario based temporal variables to generate another set of HMM state transition probability matrix. The generated HMM state transition probability matrix is then integrated with a spatio-temporal model to obtain an integrated model for predicting LULC changes to generate at least one prediction image.
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公开(公告)号：US20240096080A1
公开(公告)日：2024-03-21
申请号：US18234913
申请日：2023-08-17
Applicant: Tata Consultancy Services Limited
Inventor： Shailesh Shankar DESHPANDE , Kran Sharad Owalekar , Apoorva Khanna , Mahesh Kshirsagar , Balamuralidhar Purushothaman
IPC: G06V10/82 , G06V10/58 , G06V10/776
CPC classification number: G06V10/82 , G06V10/58 , G06V10/776
Abstract: Embodiments herein provide a method and system for a hyperspectral artificial vision for machines. The system receives a hyperspectral signal of a target material as an input to a neural network model. The system initializes by selecting the number of primitive layers to be used. The system iteratively cycles through all training data (pixels) and updating weights for each unsuccessful material class prediction. Model with two primitives serves as baseline, after which the system adds another primitive layer and repeats the training procedure. The system keeps repeating these processes until obtains convergence. Where the system come to a halt, the system obtains the optimal number of primitives for the given materials. The generated new color pixel is used as a discriminator to aid in locating the target material. The new artificial color is a mixture of weighted chromatic primitives which are optimized for sensitivity/(Spectral Response Functions) SRFs.
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9.发明申请公开(公告)号：US20200013201A1
公开(公告)日：2020-01-09
申请号：US16504196
申请日：2019-07-05
Applicant: Tata Consultancy Services Limited
Inventor： Jayavardhana Rama GUBBI LAKSHMINARASIMHA , Karthik SEEMAKURTHY , Sandeep NK , Ashley VARGHESE , Shailesh Shankar DESHPANDE , Mariaswamy Girish CHANDRA , Balamuralidhar PURUSHOTHAMAN , Angshul MAJUMDAR
Abstract: This disclosure relates generally to image processing, and more particularly to method and system for image reconstruction using deep dictionary learning (DDL). The system collects the degraded image as test image and processes the test image to extract sparse features from the test image, at different levels, using dictionaries. The extracted sparse features and data from the dictionaries are used by the system to reconstruct the HR image corresponding to the test image.
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公开(公告)号：US20190026553A1
公开(公告)日：2019-01-24
申请号：US16041438
申请日：2018-07-20
Applicant: Tata Consultancy Services Limited
CPC classification number: G06K9/00637 , G06F16/50 , G06K9/00463 , G06K9/00651 , G06K9/6269 , G06N7/00 , G06N20/00
Abstract: System and method of the present disclosure provide a linguistic approach to image processing. Prior art focused on extracting well-defined single objects occupying large portion of an image area. However, there was no focus on higher level semantics or distribution of object categories within the image. In contrast to imagery by handheld devices, remotely sensed data contains numerous objects because of relative large coverage and distribution over objects is critical to analyzing such large coverage. Accordingly, in the present disclosure, a generative statistical model is defined wherein an aerial image is modelled as a collection of the one or more themes and each of the one or more themes is modelled as a collection of object categories. The model automatically adapts to a scale of the aerial image and appropriately identifies the themes which may be used for applications including monitoring land use, infrastructure management and the like.
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