Artificial Intelligence Services
EVS has a profound expertise on Artificial Intelligence services and can work as a consulting agency as well as performing software development activities in this and related domains.
EVS can offer a variety of services in this context, including early feasibility analysis, dataset construction and annotation, model design, selection, and training, model engineering and optimization, proofs of concept, fast prototyping, and software development.
Artificial Intelligence (AI) became in the recent years the “hottest” technology trend, which is still running actively. Differently from its popular literal meaning – AI is trying to replicate human intelligence – AI aims at designing computational systems with intelligent capabilities, much more than less, associated to the processing of perceptual data such as images/video, sound/speech, or text/language. In general, AI aims at equipping artificial systems with reasoning and decision-making abilities in order to support, or also replace in some cases, humans in performing a given task.
Nowadays, AI is most of the times a synonym of Machine Learning (ML) or Deep Learning (DL), the latter characterized by the adoption a specific class of methods (i.e. deep neural networks). It is exactly Deep Learning that made AI so popular, since this type of techniques proved to be extremely well performing in a variety of applicative tasks, especially those associated to vision and speech/language.
AI/ML/DL can efficiently cope with tasks such as visual object detection and classification, scene segmentation and recognition, automatic speech translation, retrieval, image/video captioning, multimedia content generation, image and video textual description, prediction (of actions, of stock exchange, etc.), recommendations, and many others. In doing so, it does not relate to complex rules to be manually designed, but it finds and embeds such rules automatically by training, that is, learning directly from data.
Needless to say, AI and related ML and DL areas can address many application domains, including those related to the design of artificial agents or bots like robotics, video surveillance and monitoring, safety, industrial automation, entertainment (e.g., videogames, special FX), retail and fashion (selling prediction), Fintech, bioinformatics/pharma, and many others.
In this respect, EVS has specific skills and experience on machine learning, having implemented support vector machines (SVM), random forests, decision trees, as well as deep learning models such as convolutional networks, recurrent networks, auto-encoders, generative adversarial networks (GAN).
Such knowledge relates to model design, training, and validation for goals such as visual object detection, classification, semantic segmentation, and (object) recognition. EVS also worked in challenging scenarios involving unlabeled or weakly/noisy data, so addressing unsupervised learning and clustering tasks.
It is worth to notice that EVS addresses such tasks from a real application perspective since it aims at deploying reliable AI systems by leveraging robust training methods such as those related to domain adaptation and generalization, and learning with scarce data areas in general.