Abstract: Disclosed herein is method and fault detection system for detecting faults in one or more products. In an embodiment, method comprises generating plurality of wavelet coefficients corresponding to transformed images of each of the one or more products and determining a set of invariant features from the plurality of wavelet coefficients. Further, a dynamic set of invariant features is generated by grouping invariant features into a set of groups based on type of the one or more products. Subsequently, the dynamic set of invariant features is quantized based on a predetermined quantization threshold and a representative coefficient signature is associated for each group in the dynamic set of invariant features. Finally, faults in the one or more products are detected by comparing coefficient signatures associated with the one or more products with the representative coefficient signature of each group in the dynamic set of invariant features.

Abstract: This disclosure relates to method and system for providing explanation for output generated by artificial intelligence (AI) model. The method may include receiving encrypted input data and a public encryption key from a client device, wherein the encrypted input data is encrypted using the public encryption key. The method may further include generating an encrypted AI model by encrypting an AI model using the public encryption key. The method may further include generating an encrypted output and an encrypted feature data based on the encrypted input data using the encrypted AI model, and generating an encrypted explanation for the encrypted output based on the encrypted feature data. The method may further include providing the encrypted output and the encrypted explanation to the client device for rendering, wherein the encrypted output and the encrypted explanation are decrypted by the client device using a private encryption key.

Abstract: The present disclosure relate to effectively determining spatial and temporal features for extracting low-level and high-level features from image frames of a multimedia content. A plurality of image frames are received from an imaging unit. Spatial filters are applied on each image frame to generate a first set of activation maps which provide spatial features in the image frames. Further, a temporal filter is applied on the plurality of image frames at a plurality of levels to generate one or more second set of activation maps corresponding to each level for determining temporal features in the image frames. Thereafter, the spatial feature from each image and temporal feature of the plurality of image frames from each level is extracted, which represent low-level and high-level spatial and temporal features.

Abstract: A method and system for summarizing multimedia content is disclosed. The method includes the steps of extracting a set of video files from a multimedia content such that each of the set of video files comprises a plurality of frames, and summarizing each of the set of video files to generate a set of summarized video files. Summarizing includes modifying a number of frames in each of the set of video files while retaining a caption generated for each of the set of video files. The method further includes generating sets of bridge frames for the set of summarized video files, based on a deep learning model. A set of bridge frames from the sets of bridge frames maintains continuity between corresponding adjacent summarized video files. The method includes generating a summarized multimedia content based on the set of summarized video files and the sets of bridge frames.

Abstract: The present disclosure relates to method and system for performing classification of real-time input sample using compressed classification model. Classification system receives classification model configured to classify training input sample. Relevant neurons are identified from neurons of the classification model. Classification error is identified for each class. Reward value is determined for the relevant neurons based on relevance score of each neuron and the classification error. Optimal image is generated for each class based on the reward value of the relevant neurons. The optimal image is provided to the classification model for generating classification error vector for each class. The classification error vector is used for identifying pure neurons from the relevant neurons. A compressed classification model comprising the pure neurons is generated. The generated compressed classification model is used for performing the classification of real-time input sample.

Abstract: Methods and apparatus for managing configuration sessions on remotely configurable network components, and a non-transitory computer readable medium for managing configuration sessions on such components. The method includes configuring a remote configuration interface to transmit a heartbeat signal or keep alive message within a defined interval while the remote configuration interface remains operational and closing a remote configuration session on a remotely configurable network component if a heartbeat signal or keep alive message is not received within a period corresponding to the defined interval.

Abstract: The disclosure relates to method and system for training an artificial neural network (ANN) based image classifier using class-specific relevant features. The method includes receiving the ANN based image classifier, training image dataset, and various features of the training image dataset. The method further includes determining a relative relevance value of each of the features corresponding to each of the classes based on the ANN based image classifier, segregating co-occurring features from the features for each of the classes based on the training image dataset and the ANN based image classifier, identifying an imbalance in the class-specific relevant features for each of the classes based on the relative relevance value of each of the features corresponding to each of the classes, and updating the ANN based image classifier based on the imbalance in the class-specific relevant features and the co-occurring features for each of the classes.

Abstract: This disclosure relates to method, device, Wand system for clustering document objects based on information content. The method may include identifying a plurality of object chunks from at least one document based on semantic context of each of the plurality of object chunks, determining at least one document portion from the at least one document as a base document based on a plurality of parameters applied to the plurality of object chunks, determining a plurality of hierarchies within the base document, and categorizing the plurality of object chunks based on the plurality of hierarchies and information in each of the plurality of object chunks. It should be noted that each of the plurality of object chunks may include at least one object selected from the at least one document.

Abstract: A method and system for generating user driven adaptive object visualizations using Generative Adversarial Network (GAN) models is disclosed. The method includes the steps of generating a first set of object vectors for an object based on at least one input received from a user. The first set of vectors corresponds to a first set of visualizations for the object The method further includes capturing at least one tacit reaction type of the user in response to user interaction with each of the first set of visualizations, computing a score for each portion of each of the first set of visualizations, identifying a plurality of portions from at least one of the first set of object visualizations, generating a second set of object vectors, and processing the second set of object vectors sequentially through a plurality of GAN models to generate a final object visualization of the object.

Abstract: The present disclosure discloses a method and a system for generating AR/VR content in real-time. The system upon receiving a user query or gestures, identifies query attributes and action attributes associated with IOT devices. Thereafter, system identifies IOT data corresponding to the query attributes and the action attributes from the IOT devices. Based on the IOT data, system generates multimedia content using trained machine learning model. The machine learning model is trained to provide multimedia content based on the IOT data associated with the query attributes or the action attributes. Thereafter, the system generates AR/VR content in real-time based on the multimedia content. In this manner, present disclosure supports interactive queries over AR/VR content and provides AR/VR content in real-time thereby reducing storage requirement for storing various images for interpolation.

Abstract: Embodiments of present disclosure discloses system and method for managing applications in electronic device. Initially, relation tree associated with applications is identified. The relation tree is generated based on learning technique implemented for applications, parameters, enablers associated with electronic device. Based on identified relation tree, enablers are identified from plurality of enablers, corresponding to each of applications. Further, current status of parameters based on current status of enablers is retrieved. The relation tree is updated based on learning technique implemented for at least one of the current status of the parameters, new applications, new parameters, enablers associated with the electronic device. An application from the applications is identified based on the current status of the parameters and the relation tree. The electronic device is instructed to perform operations associated with the identified application.

Abstract: Disclosed herein is a method and a data transfer system for providing seamless data transfer between communication devices. Properties of data to be transferred, status of network parameters and power associated with the communication devices are monitored in real time. Further, communication protocols available at the communication devices and a need to switch between the communication protocols are determined. Splitting of the data into subsets of data and sequencing the subsets of data are performed using a neural network, which is trained based on properties of the data, data storage space of the communication devices, speed of data transfer and a communication channel available for the data transfer. The optimum communication protocols are identified based on order of priority value and contention value. The subsets of data are transferred using identified optimum communication protocols, until a change in the monitored status is detected to switch the optimum communication protocols.

Abstract: A method and dynamic learning system for providing dynamic cross learning is disclosed. The dynamic learning system identifies one or more changes in an environment in which an automated task performing device is scheduled to perform one or more activities. The dynamic learning system initiates a dynamic learning associated with the one or more changes for the automated task performing device based on pre-stored contextual information. Based on the dynamic learning, one or more actions is provided to the automated task performing device to perform the one or more activities in view of the one more changes. Therefore, the present disclosure facilitates dynamic determination and analysis of environment and situation for the automated task performing device for performing the activities. Thus, leading to dynamic decision-making to provide adjustment to the automated task performing device in any situation.

Abstract: Embodiments of the present disclosure relate to a method and an apparatus for alerting threats to users. The apparatus may capture a plurality of signals including at least one of Electro-Magnetic (E-M) signals and sound signals. The E-M signal and sound signals are used to detect objects around the user. A threat to the user is predicted based on the objects around the user and one or more alerts are generated such that the user avoids the threat. The prediction of the threat enables the user to take an action even before the threat has occurred. Also, the alerts are generated based on the prediction such that the user can avoid the threat well in advance of the occurrence of the threat.

Abstract: Disclosed herein is a method and a data transfer system for providing seamless data transfer between communication devices. Properties of data to be transferred, status of network parameters and power associated with the communication devices are monitored in real time. Further, communication protocols available at the communication devices and a need to switch between the communication protocols are determined. Splitting of the data into subsets of data and sequencing the subsets of data are performed using a neural network, which is trained based on properties of the data, data storage space of the communication devices, speed of data transfer and a communication channel available for the data transfer. The optimum communication protocols are identified based on order of priority value and contention value. The subsets of data are transferred using identified optimum communication protocols, until a change in the monitored status is detected to switch the optimum communication protocols.

Abstract: A method and system for performing real-time sentiment modulation in conversation systems is disclosed. The method includes generating an impact table comprising a plurality of sentiment vectors and a plurality of emotion vectors associated with the plurality of sentences. The method further includes generating for each of the plurality of sentences, a dependency vector based on the associated sentiment vector and the associated emotion vector. The method further includes stacking the dependency vector generated to generate a waveform representing variance in sentiment and emotions across words within the plurality of sentences. The method further includes altering at least one portion of the waveform based on a desired emotional output to generate a reshaped waveform. The method further includes generating a set of rephrased sentences associated with the at least one portion, based on the reshaped waveform, the set of sentences, a user defined sentiment output.

Abstract: A method and system for summarizing content based on user preferences is disclosed. The method includes identifying a set of relevant objects from a set of objects based on a relevancy score corresponding to each of the set of objects extracted from a plurality of sentences. The method further includes generating a link graph between each of the plurality of sentences. The method further includes assigning a weight to each of the plurality of sentences based on a retention probability. The method further includes generating a summarized content from the plurality of sentences based on the user preferences, the link graph, and the weight associated with each of the plurality of sentences.

Abstract: A system and method for identifying and subsequently modifying target sections within images is disclosed. The method includes receiving a user request that includes a target image and a user input, such that the user input includes an action corresponding to the target image. The method further includes extracting a plurality of target image attributes from the user input and comparing the plurality of target image attributes with a set of attributes within a pattern attribute table. The pattern attribute table includes mapping of each of the set of attributes to an associated set of activated neurons within a neural network. Comparing the plurality of target image further includes identifying a set of activated neurons mapped to the matching attribute as neuron activations corresponding to the plurality of target image attributes. The method includes identifying a target image section based on the set of activated neurons using a back-propagation technique.

Abstract: A method and a systems of interchanging code-mixed words and uni-language words are described. In an embodiment, the method may include identifying two or more portions of a target word, wherein the target word is one of a code-mixed word and a uni-language word. The method may further include determining one or more equivalent words corresponding to at least one portion of the two or more portions, wherein the one or more equivalent words are in at least one predetermined target language. The method may further include selecting at least one equivalent word from the one or more equivalent words, based on a context of the target word within a sentence comprising the target word. The method may further include replacing the at least one portion of the two or more portions of the target word with the selected at least one equivalent word.

Abstract: The present invention discloses a method and a system for assisting user with product handling in a retail shopping. The method comprising identifying one or more products from a list of products that user intends to purchase, neighbouring products and orientations of the one or more products and the neighbouring products from a plurality of image frames and rack information, comparing the identified orientations with historic orientations of products and neighbouring products associated with the rack information, identifying at least one product from the one or more products and the neighbouring products that is improperly oriented based on comparison, determining product safety handling instructions of the identified at least one product and assisting the user in real-time with handling of the identified at least one product based on the product safety handling instructions.