Abstract: A method and system for machine translation of text is disclosed. The method includes processing an image comprising a text to generate a pattern associated with the text based on a trained Convolution Neural Network (CNN). The method further includes mapping the pattern to a word in a mapping table and at least one text attribute, based on a classifier network. The method further includes initiating an Optical Character Recognition (OCR) conversion for the pattern, when at least one of the mapping between at least one of the pattern and at least one word in the mapping table and the mapping between the pattern and the at least one text attribute is below a predefined threshold. The method further includes performing incremental learning for the trained CNN and the classifier network based on the OCR conversion.

Abstract: This disclosure relates to method and system for classifying an object in input data using an artificial neural network (ANN) model. The method may include extracting positive features and orthogonal features associated with the object in the input data, performing a partial classification of the object based on the positive features by a first part of the ANN model, and determining an accuracy of the classification of the object based on the orthogonal features by a second part of the ANN model. The positive features are features uniquely contributing to identification of a class for the object, while the orthogonal features are features not contributing to identification of the class but contributing to identification of one or more of remaining classes.

Abstract: The present invention discloses a method and a system for rendering Augmented Reality (AR) content that adapts to changing content in a video or image. The system comprising a processor is configured to receive real-time input data from a user device, identify a plurality of objects in the real-time input data, determine association between the plurality of objects in the real-time input data and metadata of the plurality of objects, determine one or more similar associated objects from a plurality of historic objects in a database based on the determined association, select one of the one or more similar associated objects based on weightage, select at least one of an AR object and an AR action from the database for the selected similar associated objects, and render the at least one of an AR object and an AR action, with the real-time input data.

Abstract: The present invention relates to the field of content identification and more particularly to detection and identification of objectionable content present in a multimedia content. The objectionable content is detected before the upload of the content to a server or social media and it alerts the user about the presence of objectionable content based on the intelligent analytics. Further, during the alerting process the proposed mechanism is configured to consider the consequences of publishing or uploading the given content to a server or social media. Further, it also analyses the potential viewers, their profile, profile of the characters in the multimedia content.

Abstract: A method and a system are described for multimodal search key based multimedia content extraction. The method includes receiving a multimedia content search request for a multimedia content, where the search request includes multimodal inputs in one or more fragments. The one or more fragments are interleaved to a composite fragment by removing overlapping content from the one or more fragments. The composite fragment is tagged to one or more attributes associated with the multimedia content based on a deep-learning of a context associated with the composite fragment. The method further includes identifying from a multimedia content database a correlation between the composite fragment and the multimedia content based on the context, where the multimedia content is stored in the multimedia content database. The method includes extracting the multimedia content identified from the multimedia content database.

Abstract: The present invention relates to the field of dynamic content creation and management and more particularly to dynamically create and insert immersive promotional content in a multimedia. The multimedia requested by a user is procured from a media server (105) and the one or more objects present in the multimedia is determined. The content of the multimedia is analyzed, and a decision is taken to immerse the promotional content in the multimedia based on the analysis of the multimedia. Further, a promotional content is created in real time using the components present in the asset database (106) based on the personalized user profile. The created promotional content is overlaid and blended with a at least one object from the one or more objects in the multimedia. The created promotional content and the multimedia is joined to form a composite media and is streamed to the user device.

Abstract: A method of managing messages in a communication device is disclosed. The method includes receiving messages through a communication device. Critical messages may be determined by identification of one or more critical content in the one or more messages and analyzed based on the context and content associated with the critical messages. A priority for each of the critical messages may be generated by assigning vocabulary weight to the critical content and a context weight to the critical message. The critical messages may be queued based on their respective priorities. Dynamic allocation of resources by adjusting at least one of buffer, and packet delay associated with the communication device based on the priority of the one or more messages in the queue is done. The one or more messages in the communication device may be managed based on the queuing and the dynamic allocation of resources.

Abstract: A method and system for generating theme based summary from unstructured content is disclosed. The method includes assigning a sentiment category of a plurality of sentiment categories to each of a plurality of sets of words. The method further includes segregating the plurality of sets of words based on the assigned sentiment category. The method may further include processing for each of the plurality of sets of words each word in a set of words of the plurality of sets of words as a neuron in the first neural network. The method may further include determining for each of the plurality of sets of words a relevancy score for each neuron relative to an associated sentiment category. The method may further include generating a summary from the unstructured text, based on the relevancy score determined for each neuron.

Abstract: This disclosure relates to a method and system for summarizing multimedia content. The method may include receiving multimedia content. The method may further include identifying one or more primary objects, wherein identifying the primary objects comprises identifying one or more actions associated with the primary objects and one or more interactions between the primary objects and one or more secondary objects. The primary objects are associated with one or more parameters. The method may further include determining at least one primary object of interest from the primary objects by selectively prioritizing the parameters.

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: Systems and methods of providing real-time assistance to a presenter for rendering of a content are disclosed. In one embodiment, the method may include receiving a multi-modal input from the presenter with respect to the rendering of the content by the presenter, and performing a real-time analysis of at least one of the multi-modal input or a historical rendering of the content by the presenter. The method may further include dynamically determining a need for providing assistance to the presenter based on the real-time analysis. The method may further include dynamically generating, in response to the need, a supporting visual content based on the real-time analysis and a plurality of contents in a content database, and dynamically rendering the supporting visual content on a rendering device in possession of the presenter based on the real-time analysis.

Abstract: The present disclosure discloses method and a content providing system for identifying and rendering hand written content onto digital display interface of electronic device. The content providing system receives content handwritten by user using digital pointing device and identifies one or more digital objects from content based on coordinate vector formed between digital pointing device and boundary within which user writes along with coordinates of boundary. The content providing system converts one or more digital objects to predefined standard size and identifies one or more characters associated with one or more digital objects based on plurality of predefined character pair and corresponding coordinates. A dimension space required for each of digital objects is determined based on corresponding coordinate vector. Thereafter, the one or more digital objects and the one or more characters handwritten by the user are rendered in predefined standard format on digital display interface.

Abstract: The present disclosure relates to a method and a system for generating sentiment-based summaries for a user review. In an embodiment, a text analyzer receives a block of text indicating a user review. The text analyzer may generate one or more vectors for the plurality of words. Further, a relation is identified among the one or more vectors. A model is trained to identify a relation among the one or more vectors. Using the relation between the one or more vectors, a sentiment associated with the block of text is determined. Thereafter, one or more keywords from the block of text contributing to the determined sentiment is are identified and are classified into categories according to the sentiment contributed by the one or more words. Thereafter, the summary is generated for each category using the corresponding one or more words.

Abstract: The present disclosure discloses method and a content rendering system for providing multimodal content to selective users during visual presentation. The method includes identifying plurality of users attending visual presentation based on login and user details provided during registering to visual presentation. One or more keywords is determined in visual presentation associated with one or more auxiliary content based on narration by a presenter. The one or more auxiliary content corresponding to each of the one or more keywords is retrieved. The method includes identifying one or more users from plurality of users allowed to receive one or more auxiliary content based on user details and predefined auxiliary mapping details. The one or more auxiliary content is combined with corresponding one or more keywords in visual presentation. Thereafter, combined auxiliary content along with the visual presentation is provided to users in respective user devices.

Abstract: A method and system for compressing videos using deep learning is disclosed. The method includes segmenting each of a plurality of frames associated with a video into a plurality of super blocks. The method further includes determining a block size for partition of each of the plurality of super blocks into a plurality of sub blocks, based on a feature of each of the plurality of super blocks using a Convolutional Neural Network (CNN). The method further includes generating a prediction data for each of the plurality of sub blocks based on a motion vector predicted and learned by the CNN. The method further includes determining a residual data for each of the plurality of sub blocks by subtracting the prediction data from an associated original data. The method includes generating a transformed quantized residual data using each of a transformation algorithm and a quantization algorithm.

Abstract: The present invention relates to the field of content identification and more particularly to detection and identification of objectionable content present in a multimedia content. The objectionable content is detected before the upload of the content to a server or social media and it alerts the user about the presence of objectionable content based on the intelligent analytics. Further, during the alerting process the proposed mechanism is configured to consider the consequences of publishing or uploading the given content to a server or social media. Further, it also analyses the potential viewers, their profile, profile of the characters in the multimedia content.

Abstract: A method and a system are described for context based clustering of one or more objects. The method comprises receiving, by the object clustering system, receiving, by an object clustering system, an object clustering request for one or more objects associated with a plurality of contextual parameters, where the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes. It further includes tagging the one or more non-physical attributes respectively to the one or more physical attributes. It further includes identifying a common context from the one or more physical attributes associated with the one or more objects based on the tagging. It further includes mapping the one or more physical attributes to the one or more objects based on the common context. It then includes clustering the one or more objects based on the mapping.

Abstract: A method and system of identifying misclassification in a neural network is disclosed. The method includes generating for an input image, an image heatmap associated with each of a plurality of layers of a neural network. The method further includes determining for the input image, an activation value at each of the plurality of layers based on the associated image heatmap. The method includes identifying for the input image, a first pattern of triggered neurons of the plurality of layers based on the activation value generated for the plurality of layers. The method further includes comparing for each of the plurality of classes, a second pattern of triggered neurons with the first pattern of triggered neurons identified at the at least one of the plurality of layers. The method includes identifying, misclassification of the input image in the neural network based on a result of the comparison.

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 disclosure discloses a method and a threat prediction system for predicting one or more potential threats in video surveillance. The threat prediction system receives real-time video feed from video surveillance system and identifies one or more objects in a plurality of frames obtained from video feed. A scene description for each of plurality of frames is generated based on one or more objects and context associated with corresponding frames. One or more real-time actions are determined for scene based on scene description. Based on one or more real-time actions, the threat prediction system predicts one or more potential threats associated with the video feed and alerts user of the one or more potential threats based on the prediction. The present disclosure predicts one or more possible threats which may happen in near future and helps in understanding future damage and raise alerts to take preventive actions to control damage.