Image processing principles and techniques represent a significant advancement in modern technology, offering invaluable contributions to numerous sectors. Despite their efficacy, conventional AI and ML-based image processing algorithms encounter inherent limitations that obstruct their scalability and performance. The main aim of the proposed research project is to develop image processing algorithm based on quantum computing […]

This project proposal aims to tackle a significant challenge in fintech: extracting human-readable descriptions from tabular financial data. Interpreting vast amounts of structured data in the dynamic financial technology landscape is crucial for informed decision-making and compliance reporting. The project seeks to develop a robust system by leveraging open-source Large Language Models (LLMs) tailored to […]

Check fraud continues to be a substantial challenge in the financial sector, involving the unauthorized use of checks for illegal fund acquisition. To address the issue of fraud detection, specific Artificial Intelligence models, particularly Convolutional Neural Networks (CNNs), have been increasingly applied to classify checks as fraudulent or legitimate. However, there is a crucial aspect […]

This project aims to enhance subsea video quality for improved underwater visual inspection and analysis, crucial for industries like offshore oil and gas, marine research, underwater construction, and maritime security. Leveraging advanced AI and machine learning techniques, we will address challenges like water turbidity, light attenuation, and visual distortions in underwater images. Through the Lab2Market […]

Automating the extraction of handwritten text from checks is crucial for fraud detection and efficient check processing. Although Optical Character Recognition (OCR) tools like Tesseract excel with typed text, they often falter with handwritten content, causing computational inefficiencies. This project’s focus is on developing a rapid and cost-effective OCR solution tailored for handwritten text on […]

Our project aims to tackle the persistent issue of bank check fraud by using advanced deep learning technologies. By developing a system that can automatically detect fraudulent alterations in check images, we seek to enhance the security and reliability of financial transactions. This project is a collaboration with Verafin Inc., a leading provider of fraud […]

The proposed research project aims to tackle the issue of bank cheque fraud. The project will use advanced object detection AI models to accurately extract and segment bank cheques into their component fields, a crucial step in detecting fraudulent activity. These AI models will be trained to recognize specific parts of a cheque, such as […]

Ultrasound (US) is an important diagnostic tool in healthcare, especially in low- and middle-income countries (LMICs) where it is often the only available imaging modality. However, in remote and resource-limited settings, multiple barriers limit access to ultrasound including a shortage of professional sonographers and long travel distances. Teleultrasound, where non-experts perform US procedures under the […]

The ARMIS (Autonomous Real-time Mapping and Imaging System) project aims to develop an advanced indoor mapping solution utilizing cutting-edge robotics, AI, and image processing technologies to create detailed, real-time indoor maps. This system will autonomously navigate complex environments such as universities, hospitals, corporate campuses, and transportation hubs, capturing 360-degree images and processing them to blur […]

The North American livestock industry faces a combination of factors that decrease productivity, while demand for derived products continues to rise due to population growth. This necessitates the emergence of innovative, sustainable technologies to support processes, and collaborative efforts. Hence, a solution is proposed to enhance the livestock industry through an innovative IoT collar for […]

Résumé projet : SICKLE ASSIST Notre plateforme se distingue par son approche innovante, remplaçant les méthodes manuelles traditionnelles par des algorithmes d’apprentissage automatique. Ces derniers permettent une surveillance personnalisée des patients à travers les bilans biologiques, leurs complaintes, en identifiant les risques potentiels de complications et en priorisant les interventions en conséquence. En analysant les […]

Le cancer du sein représente un défi majeur en matière de santé publique et demeure la deuxième cause de mortalité chez les femmes par cancer dans le monde. Chaque année, 670 000 femmes perdent la vie à cause de diagnostics tardifs et de rechutes dans le cancer du sein, stades où malheureusement la réponse aux […]