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1.发明授权公开(公告)号：US10235642B2
公开(公告)日：2019-03-19
申请号：US15827513
申请日：2017-11-30
Applicant: Tata Consultancy Services Limited
Inventor： Ajay Kattepur , Hemant Kumar Rath , Anantha Simha , Arijit Mukherjee
IPC: G06Q10/04 , G05B19/418 , G05D1/02 , G06Q10/08
Abstract: This disclosure relates generally to autonomous devices, and more particularly to method and system to optimally allocate warehouse procurement tasks to distributed autonomous devices. The method includes obtaining, at a coordinating agent, a global task associated with the warehouse and information associated with the robotic agents. The information includes a count and status of the robotic agents. The global task is profiled to obtain a set of sub-tasks and constraints associated with the set of sub-tasks are identified. The constraints include utilization constraint and/or pricing constraints. A distributed, decentralized optimal task allocation is performed amongst the robotic agents based on constraints to obtain optimal performance of robotic agents. The distributed optimal task allocation includes performing primal or dual decomposition of the set of sub-tasks by each robotic agent and updating corresponding primal/dual variables by the coordinating agent when the optimization is performed based on utilization constraint and pricing constraints, respectively.
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公开(公告)号：US20210397878A1
公开(公告)日：2021-12-23
申请号：US17124584
申请日：2020-12-17
Applicant: Tata Consultancy Services Limited
Inventor： Arun George , Dighanchal Banerjee , Sounak Dey , Arijit Mukherjee
Abstract: This disclosure relates to method of identifying a gesture from a plurality of gestures using a reservoir based convolutional spiking neural network. A two-dimensional spike streams is received from neuromorphic event camera as an input. The two-dimensional spike streams associated with at least one gestures from a plurality of gestures is preprocessed to obtain plurality of spike frames. The plurality of spike frames is processed by a multi layered convolutional spiking neural network to learn plurality of spatial features from the at least one gesture. A filter block is deactivated from the plurality of filter blocks corresponds to at least one gesture which are not currently being learnt. A spatio-temporal features is obtained by allowing the spike activations from CSNN layer to flow through the reservoir. The spatial feature is classified by classifier from the CSNN layer and the spatio-temporal features from the reservoir to obtain set of prioritized gestures.
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公开(公告)号：US11062047B2
公开(公告)日：2021-07-13
申请号：US14900061
申请日：2014-06-09
Applicant: Tata Consultancy Services Limited
Inventor： Arijit Mukherjee , Soma Bandyopadhyay , Arijit Ukil , Abhijan Bhattacharyya , Swarnava Dey , Arpan Pal , Himadri Sekhar Paul
Abstract: This disclosure relates generally to the use of distributed system for computation, and more particularly, relates to a method and system for optimizing computation and communication resource while preserving security in the distributed device for computation. In one embodiment, a system and method of utilizing plurality of constrained edge devices for distributed computation is disclosed. The system enables integration of the edge devices like residential gateways and smart phone into a grid of distributed computation. The edged devices with constrained bandwidth, energy, computation capabilities and combination thereof are optimized dynamically based on condition of communication network. The system further enables scheduling and segregation of data, to be analyzed, between the edge devices. The system may further be configured to preserve privacy associated with the data while sharing the data between the plurality of devices during computation.
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公开(公告)号：US10776621B2
公开(公告)日：2020-09-15
申请号：US15901978
申请日：2018-02-22
Applicant: Tata Consultancy Services Limited
Inventor： Snehasis Banerjee , Swarnava Dey , Arijit Mukherjee , Swagata Biswas
Abstract: Signal analysis is applied in various industries and medical field. In signal analysis, wavelet analysis plays an important role. The wavelet analysis needs to identify a mother wavelet associated with an input signal. However, identifying the mother wavelet associated with the input signal in an automatic way is challenging. Systems and methods of the present disclosure provides signal analysis with automatic selection of wavelets associated with the input signal. The method provided in the present disclosure receives the input signal and a set of parameters associated with the signal. Further, the input signal is analyzed converted into waveform. The waveforms are analyzed to provide image units. Further, the image units are processed by a plurality of deep architectures. The deep architectures provides a set of comparison scores and a matching wavelet family is determined by utilizing the set of comparison scores.
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公开(公告)号：US10540625B2
公开(公告)日：2020-01-21
申请号：US15654151
申请日：2017-07-19
Applicant: Tata Consultancy Services Limited
Inventor： Himadri Sekhar Paul , Arijit Mukherjee , Arpan Pal , Ansuman Banerjee
Abstract: A system and method for determining a configuration of a plurality of tasks to meet the specified deadline of a linear workflow of a real-time heterogeneous network. Often times, while meeting expected application performance in the heterogeneous network, it may possible to have graceful degradation of quality for ensuring timing constraints at the same time. In a multi-layered architecture, where each layer is equipped with multiple computational resources, the time optimization for each of the plurality of tasks can be achieved through approximate computing and analyzing all possible configurations of each task in a workflow within a particular layer.
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Patent Agency Ranking
公开(公告)号：US10511543B2
公开(公告)日：2019-12-17
申请号：US15901963
申请日：2018-02-22
Applicant: Tata Consultancy Services Limited
Inventor： Sounak Dey , Arijit Mukherjee , Abhijan Bhattacharyya , Arpan Pal
IPC: G06F15/173 , H04L12/911 , G06F17/27 , B25J9/16 , H04L29/08
Abstract: Systems and methods of the present disclosure enable exchange of semantic knowledge of resource data and task data between heterogeneous resources in a constrained environment wherein cloud infrastructure and cloud based knowledge repository is not available. Ontology based semantic knowledge exchange firstly enables discovery of available resources in real time. New tasks may evolve at runtime and so also resource data associated with the resources may vary over time. Systems and methods of the present disclosure effectively address these dynamic logistics in a constrained environment involving heterogeneous resources. Furthermore, based on the required resource data for each task and the available resources discovered in real time, task allocation can be effectively handled.
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公开(公告)号：US20180025301A1
公开(公告)日：2018-01-25
申请号：US15654151
申请日：2017-07-19
Applicant: Tata Consultancy Services Limited
Inventor： Himadri Sekhar PAUL , Arijit Mukherjee , Arpan Pal , Ansuman Banerjee
CPC classification number: G06Q10/0633 , G06F9/5066 , G06Q10/04
Abstract: A system and method for determining a configuration of a plurality of tasks to meet the specified deadline of a linear workflow of a real-time heterogeneous network. Often times, while meeting expected application performance in the heterogeneous network, it may possible to have graceful degradation of quality for ensuring timing constraints at the same time. In a multi-layered architecture, where each layer is equipped with multiple computational resources, the time optimization for each of the plurality of tasks can be achieved through approximate computing and analyzing all possible configurations of each task in a workflow within a particular layer.
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公开(公告)号：US20150163289A1
公开(公告)日：2015-06-11
申请号：US14498619
申请日：2014-09-26
Applicant: TATA CONSULTANCY SERVICES LIMITED
Inventor： Himadri Sekhar Paul , Arijit Mukherjee , Swarnava Dey , Arpan Pal , Ansuman Banerjee
IPC: H04L29/08
CPC classification number: H04L67/10 , G06F9/5066 , G06F2209/5017 , H04L43/0811 , H04L43/0817 , H04L67/02
Abstract: A method for data partitioning in an internet-of-things (IoT) network is described. The method includes determining number of computing nodes in the IoT network capable of contributing in processing of a data set. At least one capacity parameter associated with each computing node in the IoT network and each communication link between a computing node and a data analytics system can be ascertained. The capacity parameter can indicate a computational capacity for each computing node and communication capacity for each communication link. An availability status, indicating temporal availability, of each of computing nodes and each communication link is determined. The data set is partitioned into subsets, based on the number of computing nodes, the capacity parameter and the availability status, for parallel processing of the subsets.
Abstract translation: 描述了在物联网（IoT）网络中进行数据划分的方法。 该方法包括确定能够有助于处理数据集的IoT网络中的计算节点的数量。 可以确定与IoT网络中的每个计算节点相关联的至少一个容量参数以及计算节点和数据分析系统之间的每个通信链路。 容量参数可以指示每个计算节点的计算能力和每个通信链路的通信容量。 确定每个计算节点和每个通信链路的可用性状态，指示时间可用性。 基于计算节点的数量，容量参数和可用性状态，数据集被划分为子集，用于子集的并行处理。
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公开(公告)号：US11967133B2
公开(公告)日：2024-04-23
申请号：US17450602
申请日：2021-10-12
Applicant: Tata Consultancy Services Limited
Inventor： Swarnava Dey , Jayeeta Mondal , Jeet Dutta , Arpan Pal , Arijit Mukherjee , Balamuralidhar Purushothaman
IPC: G06V10/00 , G06V10/44 , G06V10/764 , G06V10/82
CPC classification number: G06V10/764 , G06V10/454 , G06V10/82
Abstract: Embodiments of the present disclosure provide a method and system for co-operative and cascaded inference on the edge device using an integrated Deep Learning (DL) model for object detection and localization, which comprises a strong classifier trained on largely available datasets and a weak localizer trained on scarcely available datasets, and work in coordination to first detect object (fire) in every input frame using the classifier, and then trigger a localizer only for the frames that are classified as fire frames. The classifier and the localizer of the integrated DL model are jointly trained using Multitask Learning approach. Works in literature hardly address the technical challenge of embedding such integrated DL model to be deployed on edge devices. The method provides an optimal hardware software partitioning approach for components or segments of the integrated DL model which achieves a tradeoff between latency and accuracy in object classification and localization.
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10.发明公开公开(公告)号：US20230334300A1
公开(公告)日：2023-10-19
申请号：US18080097
申请日：2022-12-13
Applicant: Tata Consultancy Services Limited
Inventor： Dighanchal BANERJEE , Arijit Mukherjee , Sounak Dey , Arun George , Arpan Pal
Abstract: The present disclosure relates to methods and systems for time-series classification using a reservoir-based spiking neural network, that can be used at edge computing applications. Conventional reservoir based SNN techniques addressed either by using non-bio-plausible backpropagation-based mechanisms, or by optimizing the network weight parameters. The present disclosure solves the technical problems of TSC, using a reservoir-based spiking neural network. According to the present disclosure, the time-series data is encoded first using a spiking encoder. Then the spiking reservoir is used to extract the spatio-temporal features for the time-series data. Lastly, the extracted spatio-temporal features of the time-series data is used to train a classifier to obtain the time-series classification model that is used to classify the time-series data in real-time, received from edge devices present at the edge computing network.
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