• Tagging Artist in video timeline for view information(face detection ,recognition and tracking )

• Digitizing Credits scenes by delivering systematic correlation between title and artist name in .csv format.

• Optimizing deep learning algorithms to achieve 3 fold optimization with CPU-GPU hybrid architecture.

• Edge deployable solution for building management systems(Nvidia Jetson tx2 & Nvidia Nano ).

• Face detection and logging on the shop floor .

• Attendance management and access control

• Person detection and tracking for floor management .

• Document analysis tool Development for segregation of area in a page . i.e., Tabular , Text block , charts , Figure or Engineering drawing .

• Object detection and identification

• Text detection and Optical character recognition

• Natural language processing(NLP) for extraction of Domain specific data from Technical specification documents .

Product - DCREST is a Web Based Platform which supports HSBC Bank by providing insights from the documents which are source from customer. Documents such as Business license Certificate of incorporation etc. also related parties documents such as DL PAN AADHAR contains information which are required for onboarding journeys. Extracting such information form documents is time consuming and costly. DCREST is a standalone platform which provides API/Web interface for extracting information

Product – AiKno is an AI platform catering to varies need of Engineering domains such and Engineering drawing digitization Specification Extraction Digital Media (Video Text) Extraction Surveillance etc.

Product –Loop Sensor is an Intelligent VMS (Video Management System) with AI capabilities. Frames streamed from Class rooms CCTV are used for attendance and tracking of individuals with the time stamp.

Project – Number plate segmentation and license number recognition integrated with speed measuring system.

Project – Imaging a spectrum from different layer of crystal to get localized density of different elements. Use image processing to detect density variations of a particular element of interest in real time.

Project – Developing a Deep learning-based Defect Detection Application for automating the Test Procedure based in the ASNT inspection standards. Detects can be detected by Imaging techniques such as Ultrasound and Radiography.

Product –Signal Processing using Deep learning on Ultrasonic Spectroscopic and eddy current systems and raising alters for defects in metals products.