Computer Vision Solutions

Derive Meaningful Insight from Your Visual Data

Reasons to Adopt Computer Vision Services

There are distinct reasons why computer vision technologies are being adopted by businesses. The two primary reasons are reducing human errors in analyzing visual data and saving time by faster processing large amounts of visual data. Now, these two reasons apply to various domains, including manufacturing, healthcare, automotive, energy, oil, and gas industries.  

At ThirdEye Data, we have built over 25 computer vision applications and successfully implemented them in real-world use cases. These computer vision solutions are adopted by some of the Fortune 500 companies from various industries. 

Companies Who Implemented Our Computer Vision Solutions

Segments of the Computer Vision Solutions We Offer

Object Detection

Object detection is one of the primary segments of computer vision solutions that focuses on identifying and locating objects within the ingested images or videos. It can distinguish different object types within the frame with the help of Convolutional Neural Networks or CNNs. As CNNs process the image, the model learns to identify patterns and shapes that correspond to specific objects.
This segment is used in applications like retail product identification, product quality checking, asset inspection, safety protocol monitoring, self-driving cars, and security surveillance.

Image Classification

In image classification, the entire image is classified into a single category based on its content. The algorithm identifies and extracts key characteristics from the training data. Like object detection, CNNs are trained on labeled images for classification. Post-training, the model learns to recognize the patterns and relationships between features that distinguish different categories.
This segment of computer vision solutions is often used for tasks like image organization, content moderation, and medical and satellite image analysis.

Image Segmentation

This segment of computer vision solutions goes one step further than object detection. It assigns a specific category to every single pixel in the frame and creates a pixel-wise breakdown of the image. We use deep learning algorithms, like Fully Convolutional Networks (FCNs).
The applications of image segmentation include medical image analysis like segmenting tumors from the diagnostic report, obstacle identification for self-driving cars by segmenting pedestrians & roads, and self-learning navigational features of autonomous robots.

Facial Recognition

This specialized segment of computer vision services focuses on identifying and verifying individuals based on facial features like eyes, nose, and mouth to create a unique "facial signature" for each person. We use deep learning architectures specifically designed for facial recognition.
Facial recognition technology is used in social media platforms, law enforcement, and security applications.

Action Recognition

This segment of computer vision solutions analyzes sequential visual data like video footage to identify and classify actions, taking place in the frame. Recurrent Neural Networks (RNNs) are used for action recognition due to their ability to process sequential data and capture temporal dependencies between frames.
It is primarily used in detecting suspicious activity in surveillance footage and commentary of games.

Image Captioning

Image captioning solutions automatically generate a textual description of an image. It analyzes the content and creates captions summarizing the scene or objects in the frame. This segment of computer solutions uses deep learning models, like CNNs that combine with natural language processing or NLP techniques.
This segment is getting popular for enhancing image search functionalities, building smart retail solutions, and developing applications for visually impaired users.

Customer Success Stories

Image Processing System to Detect Anomalies in Electric Poles

Building an AI-powered platform that can detect the quality of the third-party provided electric poles' images and process them for anomaly detection to avoid potential hazards.

AI Floor Generation, 3D Modeling and Interior Design Software

A design firm aimed to develop an AI-powered interior design software to automate and streamline the design process. We developed a compact software powered by the latest Generative AI technologies.

Order Management System for Enhancing Efficiency and Customer Engagement

Developed a next-generation order management system for a leading oilfield equipment and services provider. The objective was to enhance operational efficiency, improve customer engagement.

Technologies We Use to Build Computer Vision Solutions

Data Acquisition: Cameras, Smartphones, Drones, Sensors  

Data Annotation or Labelling: Labelbox, VGG Image Annotator or VGG IA  

Deep Learning Frameworks: TensorFlow, PyTorch, Keras   

Neural Networks: Convolutional Neural Networks or CNNs, Recurrent Neural Networks or RNNs, Fully Convolutional Networks or FCNs  

Pre-trained Models: VGG, ResNet   

Cloud Platforms: Microsoft Azure, Google Cloud Platform or GCP, Amazon Web Services or AWS  

Visualization: TensorBoard, Neptune

Containers: Docker, Kubernetes  

APIs: OpenCV

Unlock Hidden Insights from Your Visual Data with Bespoke Computer Vision Solutions

Whether you want to explore the scope of implementation or build a computer vision application from scratch, ThirdEye Data can help. Talk to our AI engineers for free and schedule a consultation session to discover how customized CV solutions can help you achieve your business goals. Let us help you see the bigger picture and unlock the hidden insights within your visual data.

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