Veveo, Inc.

Sigtuple Technologies Private Limited

Apurv Anand

Murali Aravamudan

Sashikumar Venkataraman

Rakesh Barve

Vineet Agarwal

Pankaj Garg

Keyur Faldu

Tathagato Rai Dastidar

Bharath Cheluvaraju

Rohit Kumar Pandey

Abdul Aziz

Dheeraj Mundhra

Shreepad Potadar

Abhishek Shukla

Amrutha Muralidharan

Deepak Kapoor

Vijay Muralidharan

Nivedita Muthusubramanian

Karan Dewan

Apoorva Jakalannanavar Halappa Manjula

Harshit Pande

Raghu G

The present disclosure provides user-interface methods and systems for submitting search requests to search engines and presenting search results therefrom customized using content preferences learned about a user, comprising sending query information to at least two search engines, including a query identifying desired content, and user information, including context information describing the environment in which the query information is being sent, and a user signature representing content preferences learned about the user; receiving at least one set of a search result and auxiliary information from the at least one search engine in response to sending the query information, including information describing attributes of the search result that led to the search result being chosen by the at least one search engine; ordering the at least one search result based at least in part on the auxiliary information; and presenting the ordered search results to the user.

Method of and system for conducting personalized federated search and presentation of results therefrom

Embodiments of present disclosure discloses system and method for reconstruction of FOV. Initially, presence of one of single object and distinct objects in FOV of image of sample comprising one or more objects is determined based on sharpness of one or more objects. A single optimal representation of FOV may be generated when presence of single object is determined. At least one of single optimal representation and a depth-based enhanced representation of FOV may be generated when presence of distinct objects is determined. For generating depth-based enhanced representation, one or more first optimal images associated with each of distinct objects in FOV may be retrieved. An optimal representation of each of distinct objects is generated based on corresponding one or more first optimal images. Further, optimal representation of each of distinct objects is placed at corresponding optimal depth associated with respective distinct object to generate depth-based enhanced representation.

Method and system for reconstructing a field of view

Disclosed subject matter relates to Peripheral Blood Smear (PBS) that determines an area to be scanned in PBS for analysis. A PBS analysing system captures a focused image at each of plurality of positions in the PBS and determines Quality Indicators (QIs) in focused image. Further, a region is identified in PBS where QIs of focused image satisfy predefined QI threshold limits, as a monolayer region of PBS and determines an initiation point in monolayer region based on cell count value and co-ordinates of each of the plurality of positions located in the monolayer region. Finally, the area to be scanned in monolayer region is determined based on the initiation point and a predefined scan pattern. Determining the area to be scanned yields accurate and faster results.

Method and system for determining area to be scanned in peripheral blood smear for analysis

Disclosed herein is method and system for determining quality of semen sample. Trajectories of objects, identified in each of plurality of image frames of semen sample, are generated by tracking movement of the objects across image frames, and compensating a drift velocity of the semen sample. Further, generated trajectories are classified into sperm and non-sperm trajectories. Finally, total concentration estimate and total motility estimate of the semen sample are computed to generate a semen quality index, which indicates quality of the semen sample. In an embodiment, the method of present disclosure uses a multi-level Convolutional Neural Network (CNN) analysis technique for effectively classifying the object trajectories into sperm and non-sperm objects. Also, since the present method includes estimating and compensating drift velocity in the semen sample, it enhances overall accuracy of motility estimation and semen quality analysis.

Method and system for determining quality of semen sample

Embodiments of present disclosure discloses system and method for acquisition of optimal images of object in multi-layer sample. Initially, images for FOV of multi-layer sample comprising objects are retrieved. Each of images are captured by varying focal depth of image capturing unit associated with system. Further, objects associated with multi-layer sample in FOV are identified. For identification, cumulative foreground mask of FOV is obtained based on adaptive thresholding performed on foreground image of FOV. Based on contour detection performed on cumulative foreground mask of FOV, object masks, corresponding to objects, is obtained for identifying objects. Further, sharpness of each of images associated with each of object masks is computed. Based on sharpness, optimal images from images for each of objects is selected for acquisition of optimal images of objects in multi-layer sample.

Method and system for acquisition of optimal images of object in multi-layer sample

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Bengaluru, India

Apurv Anand