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Spearheaded the development YOLO models to detect copyright infringements in merchandise across 8 ECA clubs, 5 NBA teams, and 14 kit manufacturers, achieving a 99% reduction in image processing costs.

Delivered over $5k in monthly savings while processing ~3 million images by transitioning from Google Vertex API to cost-effective in-house models, optimizing performance and deploying on AWS Lambda for scalable, high-eﬀiciency operations.

Developed a deep learning pipeline to accurately identify fake documents (>90% accuracy) and improved OCR efficiency by 60%, significantly reducing costs and enhancing efficiency.

Contributed to a cutting-edge text analysis solution for a top collectibles marketplace app, enhancing user experience on iOS and Android.

Assisted in creating innovative Generative AI course content for OpenCV, focusing on Prompt Engineering, securing over $150k in Kickstarter funding.

Big Vision partners with growth-focused brands to drive value for every client partner.

Our business-first approach powers our capabilities across branding, marketing, and technology. Collaborative workshops and ethnographic research draw out critical insights that guide our work. Technology and automation drive our comprehensive brand solutions to deliver results rapidly and at scale.

Our experience and your expertise come together to bring your future into focus.

Big Vision is a consulting organization with expertise in advanced Computer Vision & Artificial Intelligence (AI) research and development.

Worked on an IMPRINT project funded by the Government of India, focusing on segmenting the Optic Disc and Optic Cup. 

Collaborated with QPIAI to develop a cloud-based AI healthcare platform.

Trained UNet models to segment gastrointestinal disorders and abnormalities in images from wireless capsule endoscopes, in a project supported by the Bill & Melinda Gates Foundation.

IKP Knowledge Park

BIRAC

Startup Karnataka

The Indian Institute of Science (IISc) was founded in 1909 as a result of the joint efforts of Jamsetji Nusserwanji Tata, the Government of India, and the Maharaja of Mysore. In 1886, Jamsetji Tata conceived of a university of science that would work for the benefit of India, and in 1898 created an endowment for establishing such an institution. The Government of India then took up the effort, and, in consultation with scientists in England and in India, decided to locate the Institute in Bengaluru, where the Maharaja of Mysore, Shri Krishnaraja Wodeyar IV, donated 372 acres of land. The Institute was formally vested in 1909, the foundation stone was laid in 1911, and the first batch of students started their studies in the same year.Over the last century, IISc has become the premier institute for advanced scientific and technological research and education in India. Beginning with 2 departments and 21 students in 1911, today IISc has 39 departments, units, or centres, 3500 students, and about 500 academic and scientific staff, supported by 600 administrative personnel. About 2200 students are in various PhD programs, almost 900 are enrolled for various Masters degrees, whereas about 400 are registered in the newly established, research oriented, four-year Bachelor of Science (Research) programme.In recent years, the Institute has vigorously promoted interdisciplinary research. New centres such as the CiSTUP, the Robert Bosch Centre for Cyber Physical Systems and a new Centre for Brain Research (funded by a large private endowment) are expected to conduct translational research in their respective areas, in order to better connect with industry and society. With the recent construction of modern buildings, acquisition of new research facilities, and induction of a large number of new faculty members, the Institute can look forward to an era of high productivity, increasing impact, and rising prominence in the world.

College offering multiple degrees & courses in engineering stream

I had the privilege to work on an exciting project that aimed to propose an automated method for segmenting the lumen intima layer of the common carotid artery in longitudinal mode ultrasound images. The proposed hybrid approach used active oblong optimization, median filtering, Canny edge detection, and smooth curve fitting to accurately delineate the carotid artery.

I collaborated with expert radiologists from Kasturba Medical College, Manipal, to validate the proposed technique on 84 longitudinal mode carotid artery ultrasound images provided by the Signal Processing Laboratory, Brno university. The results were remarkable, with an average accuracy and Dice similarity index of 98.9% and 95.2%, respectively.

Through this experience, I gained expertise in image processing, algorithm development, and validation. I also honed my ability to work collaboratively, adapt to new challenges, and communicate technical concepts effectively.

I am proud to have contributed to this project, and the proceeding is published in one of the top medical imaging processing venues, the 42nd Annual International Conference of IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2020).

Manipal Institute of Technology, also known as ManipalTech or M.I.T. Manipal is a privately funded school of engineering and technology located in Manipal, Karnataka, India. It was formerly known as Manipal Engineering College (MEC).

It is one of the constituent colleges that make up Manipal Academy of Higher Education (MAHE), (formerly, Manipal University), based in Manipal. It awards undergraduate,graduate and doctoral degrees in various fields of study to students from all over the world.

A sister concern of the institute, located in Sikkim, India, was established in 1995 under the ambit of Sikkim Manipal University. International engineering programs, operating out of the campus located in the city of Dubai, United Arab Emirates were established in 2008[

Manipal Institute of Technology is a school.

AI and Computer Vision Engineer | Deep Learning, Machine Learning

Abhijeet Dhupia

We propose an automated method for the segmentation of lumen intima layer of the common carotid artery in longitudinal mode ultrasound images. The method is hybrid, in the sense that a coarse segmentation is first achieved by optimizing a locally defined contrast function of an active oblong considering its five degrees-of-freedom, and subsequently the fine segmentation and delineation of the carotid artery are achieved by post-processing the portion of the ultrasound image spanned by the annulus region of the optimally fitted active oblong. The post-processing includes median filtering and Canny edge detection to retain the lumen intima representative points followed by a smooth curve fitting technique to delineate the lumen intima boundary. The algorithm has been validated on 84 longitudinal mode carotid artery ultrasound images provided by the Signal Processing laboratory, Brno university. The proposed technique results in an average accuracy and Dice similarity index of 98.9% and 95.2%, respectively.