Computer Vision
Bring Your Digital Images To Life, Gain Deeper Insights, And Stay Ahead Of The Curve With Our Cutting-Edge Computer Vision Solutions
With the massive amount of digital data created these days as text, audio, video, and photos, companies must equip themselves to handle growing analytics-driven needs.
At Valiance, we leverage advanced computer vision solutions to automate the identification of people, places, and objects of interest. Our deep learning models effortlessly extract, analyze, classify, and comprehend valuable information from images and video sequences with outstanding accuracy and speed. We offer several high-value applications across industries, including railways, power utilities, wild life conservation, public safety, logistics, and more.
Why Computer Vision?
Save Costs
Computer vision automates labor-intensive operations, saving money and improving efficiency. It decreases errors and increases quality control and inspection accuracy. It also optimizes energy and raw material utilization, lowering expenses.
Enhance Productivity
Automation frees up staff to work on more complex and creative tasks. Real-time insights and data analysis help organizations make better choices and improve accuracy and productivity. It also boosts production and productivity, thereby improving both profitability and efficiency.
Accelerate Innovation
Stay ahead of the competition by automating processes, generating insights, and speeding up innovation. Firms can learn from visual imagery and apply new ideas, while image and video analysis inspire new goods and services.
Take Preventive Action
Computer vision leverages real-time analysis to minimize operational risks and take preventive action. Proactively detect production faults and safety issues, identify patterns and anomalies, monitor social media and consumer feedback, and swiftly improve procedures.
Use Cases
Virtual Fencing
Species Identification
Object Recognition And Tracking
Quality Control And Inspection
Virtual Fencing
Virtual fencing, a promising computer vision application, creates virtual borders for livestock management, animal protection, and worker safety. It provides effective and trustworthy solutions for varied sectors with real-time monitoring and automated alarm systems.
Manage livestock in grazing regions, provide safe zones for wildlife near human settlements, avert human-animal conflict, and alert local authorities when animals approach the boundary. By establishing a digital boundary or virtual fence using cameras and sensors, you can monitor and analyze the camera feed and detect movement within the designated area. Virtual fencing can also protect construction workers from injuries.
Species Identification
Our computer vision solution is a powerful tool for understanding the natural world and informing conservation efforts. Using computer vision to identify species can assist biologists, ecologists, and conservationists in automatically detecting and classifying varied flora and wildlife, protect endangered species by assessing their visual characteristics and preserve ecosystems. Seamless animal population monitoring and ecosystem health analysis simplify wildlife management and equip you with insights into habitat loss, climate change, and the impact of human activities on the environment.
Partner with us to enhance your insights while protecting the natural world.
Object Recognition And Tracking
Incorporate powerful object recognition and tracking capabilities to detect security threats and intercept potential breaches in airports and other high-security areas. Robotics and autonomous cars can also benefit from object identification and tracking. You can offer real-time object identification and tracking by evaluating and monitoring visual characteristics and patterns, improving surveillance, navigation, and decision-making. In the retail industry, our object recognition and tracking solution helps monitor customer behavior, analyze shopping patterns, and optimize store layouts and product placement to increase sales.
Quality Control And Inspection
Leverage the power of computer vision to optimize your operations and ensure the highest standards for products and materials by enabling real-time image and video footage analysis, detecting defects and irregularities, and monitoring production lines in manufacturing. Analyzing visual patterns and features helps you quickly identify product defects or flaws in manufacturing and minimizes the need for human inspection. In construction, our technology identifies safety hazards, such as debris or obstacles, and ensures worker safety.
Case Studies
Video Based Defect Identification for Foam manufacturing unit
Client Background
The customer is an industry-leading polyurethane (PU) foam producer, and their facilities can be found nationwide, It produces foams for mattresses used in homes, the auto industry, and hospitals.
Business Objective
The company’s quality inspection process was completely manual and required multiple people to keep a constant vigil on the foam output, leading to limitations on machine output and a 3% bad sample rate.Since machines ran at sub-optimal speeds and required intensive manual intervention, it was required to automate the quality control process and reduce defects by optimizing Al & computer vision.
Our Winning Moves
- A sulte of loT-enabled video cameras across one unit to observe the output foam and flag any abnormalities. Were deployed
- The solution included camera units with local connectivity, a local internet gateway, and dashboard to monitor defects identified by ML algorithms.
- Training data from the manufacturing plant was used to train deep-learning classification models on the AWS cloud with a 95-99% recall rate across different defect categories.
- ML models were exposed through API gateway, Kinesis stream, and lambda functions to detect defects in the incoming video feed.
Outcome
- Observed promising results within 1 month
- 5% increase in throughput
- Less than 1% of humanly identifiable defects
Wildlife Species Identification From Video Feed
Client Background
Client is intemationally acclaimed Institution which is actively engaged in research on biodiversity related issues. Their mission is to nurture the development of wildlife science and promote its application in conservation, in consonants with our cultural and socio-economic milieu.
Business Objective
- To develop an image classification engine to identify Himalayan animal species using motion-sensing cameras, The species included Snow Leopard, Wooly Hare, Marmot, Ibex, and Blue Sheep. They sought a service provider.
- To build an image classification model to identify and classify newly-captured images of species using historical data.
- To help users correctly identify the species in captured images, eliminate misclassified images, and retrain the model from the last checkpoint with the correct classification.
Our Winning Moves
- We proposed a platform to intelligently identify Himalayan wildlife species in captured images and retrain the backend model using new and labeled data.
- Tagged images were uploaded to AWS S3 storage and transformed into a feature matrix using transfer learning on pre-trained deep learning-based models.
- The model was trained to predict the Image tag (animal species) using the generated feature vectors.
- Model weights were stored on AWS S3 and made accessible using a web-based application.
- The application generated predictions for new image data using a REST API.
- ‘The new image data could be incorporated into the model for retraining.
Outcome
- 89.6% overall accuracy in identifying and predicting species from the given pool.
Unlock the Power of Your Visual Data: Contact Us for Computer Vision Solutions!
Speak To Our Experts
