Optimizing business processes by extracting real-time data from images and videos
Computer Vision detects and extracts rich data from images or objects, categorizes, and processes the information to give actionable insights. These systems do not require devices to be embedded, physically printed, or externally attached to the objects targeted for detection. Computer Vision Services enable enterprises with faster, accurate, outstanding and skillful outcomes by quantitatively measuring structured data.
We deploy advanced technologies like Deep Learning and Artificial Intelligence to extract data from images and videos to provide custom Computer Vision solutions. We ensure our clients with measurable business results with our intelligent Computer Vision models. With a customized approach, our Computer Vision developers work with specifically targeted businesses while paying attention to their specific needs.
Our cutting-edge services in computer vision and image processing make us the pioneer in designing superior algorithms. We provide optimized solutions for achieving maximum accuracy. We seamlessly integrate Computer Vision technology into your product, service, application, or processes to drive value for your business.
We customize our Image Recognition services as per the specific needs of our clients and help them automate their processes by efficiently extracting data from images and videos. Our Image Recognition models extensively leverage AI and Machine Learning technologies to facilitate services like –
We ensure that our cost-effective and time-saving models are highly accurate and reliable, and help our clients in releasing breakthrough AI-based solutions for the real world and transform their businesses.
Image Segmentation technology is broadly used in image processing, face recognition, pedestrian detection, etc. We, at Soulpage IT Solutions, use deep learning to easily create robust and reproducible segmentation results for our clients. Few areas where our Image Semantic Segmentation solutions can be leveraged are –
Soulpage IT Solutions provides scalable, real-time and modular Image Reconstruction solutions to our clients. Our models are equipped with a wide range of features that support communication, peripheral devices, displays, and multi-channel synchronization. Our highly professional team develops generative models, which mimic the distribution of data, broadly on 3 approaches :
Generative Adversarial Networks (GANs) – GANs are two neural networks competing against each other. Few applications and use cases of our GANs are single image high resolution, object detection, text to image synthesis, medical image analysis, anomaly detection, 3D object recognition, video generation, etc.
Variational Autoencoders (VAEs) – The encoder and decoder networks in our models convert the inputs into smaller representations, and convert them back to the original input. Featured use cases of our Autoencoders are dimensionality reduction, image denoising/noise removal, image compression, image generation, feature extraction, sequence to sequence prediction, etc.
Autoregressive models – Our solutions train a network that models the conditional distribution of every individual pixel given by previous pixels. Few applications include image segmentation, 2D image processing, etc
Our trained AI driven biometric model captures 32 facial dots and generates 128-dimensional vector embedding which is matched during live streaming. Based on a Deep Neural Network, called FaceNet, our solution is built on advanced techniques of Computer Vision and Image Processing. This model benefits in preventing crimes apart from easing out the tedious task of marking attendance in schools, colleges, and offices.
Our AI-driven software detects 14 pathologies in less than 5 seconds. The CNN model-based algorithm reads the uploaded x-ray image without any human support and can identify the affected areas by heat mapping, thereby alerting the radiologists. ChestX gives accurate results (with 90% accuracy) in identifying the ailments and results in improved treatments, reducing human errors, and boosting patient satisfaction.
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