Computer Vision Software Development

Our team specializes in video analytics, which involves meticulously examining digital images and videos. This process enables us to perform diverse tasks, such as counting the number of individuals in a video or identifying specific objects and individuals within it.

We identify and track objects within images and videos and label them with relevant information with methods like object detection, object tracking, and object labeling.

Chatbots can collect valuable customer data, such as preferences and purchase history, providing businesses with insights for marketing and sales strategies.

We can assign one or more relevant labels to raw data, such as images, text files, and videos, to provide additional context, enabling machine learning models to learn from the data and to make accurate predictions or classifications.

We extract text from images with Optical Character Recognition (OCR) and Intelligent Character Recognition (ICR), thereby eliminating the need for manual data input.

We annotate images with descriptive labels or tags to improve machine-learning model accuracy through object recognition, image segmentation, and bounding box labeling.

With GAN, we can generate new data instances that closely resemble existing data, e.g. we can create images that resemble photographs of human faces, even though the faces depicted may not belong to any actual person.

With CBIR, we can search and retrieve images from a database. We input a query image and are presented with a selection of images from the database that share similarities with the query image. The system achieves this by analyzing the database to find the most similar ones.

We detect and recognize human emotions from visual cues, such as facial expressions, body language, and tone of voice. This helps us understand better and respond to human emotions in various applications, such as marketing, healthcare, and entertainment.