Synthetic Computer Vision (SCV) is an emerging technology that combines computer-generated imagery (CGI) and machine learning to train models in understanding visual information. In SCV, the emphasis is on employing artificially generated data instead of solely relying on real-world data.
This approach has several benefits compared to traditional computer vision methods:
- Speed of Execution: Synthetic data can be generated in a fraction of the time at scale.
- Scalability: SCV can be used to generate synthetic data for virtually any scenario. It also eliminates the time and cost associated with human labelling in traditional image recognition (IR), often known as ‘Human in the loop’.
- Accuracy: SCV models can be trained using synthetic data, to achieve a higher level of diverse data sets. This gives it superior accuracy than models trained on real-world data because it’s not limited by the constraints of the real world. Synthetic data can be generated using a much wider range of lighting conditions, backgrounds and object placements which is particularly important in challenging environments such as pharmacies and in specialty retail.
Harnessing its competitive advantages, SCV finds diverse applications across a spectrum of industries, including:
- Revolutionising TransportationFuelling the evolution of self-driving cars, SCV is instrumental in training models to adeptly recognise and respond to a myriad of scenarios - be it identifying pedestrians, cyclists, other vehicles, or deciphering traffic signs.
- Advancing HealthcareIn the realm of medical imaging, SCV takes centre stage, empowering models to discern and diagnose diseases with precision, tackling challenges in areas such as cancer and heart disease.
- Empowering RoboticsSCV serves as the backbone for training robots, enabling them to navigate and seamlessly interact with the dynamic environment surrounding them.
- Enhancing Manufacturing Within the manufacturing landscape, SCV plays a crucial role by training quality control models to detect imperfections and defects in products, ensuring a higher standard of manufacturing excellence.
- Transforming Retail In the retail sector, SCV is a game-changer, training models to meticulously track inventory, identify out-of-stock items, and strategically optimise product placement for an elevated shopping experience.
- Elevating Agriculture Practices SCV extends its impact to agriculture, where it trains models to detect and combat pests and diseases in crops, while also monitoring and enhancing overall crop growth.
In transforming retail execution through SCV, we've had the privilege of witnessing our CPG clients achieve remarkable success. A noteworthy example is our collaborative journey with Sagra Technologies, where their Image Recognition capabilities were significantly enhanced.
Together, we achieved the following milestones for Sagra Technologies:
- Facilitated a swift transition from onboarding to project delivery in just 7 days.
- Seamlessly integrated with their SFA System, boosting overall operational efficiency.
- Powerful image recognition able to provide distinctions between nearly identical SKUs.
For Consumer Packaged Good (CPGs) brands, grappling with challenges in data and technology, SCV emerges as a transformative ally, offering the key to overcoming these hurdles.
CPGs are being held back from competing for a variety of reasons but two of the most significant are a lack of adequate insights and technology. Let’s explore how SCV is proving instrumental in effectively addressing and resolving both of these critical challenges.
Adequate Insights
In the realm of SCV, leveraging synthetic image recognition powered by artificial data is a game-changer. Unlike traditional models reliant on real-world data, SCV benefits from synthetic data created through virtual reality - artificial images or videos. This not only simplifies the learning process for SCV models but also holds the unique advantage of synthetic data remaining undiminished over time. This contributes to improved accuracy and more reliable insights for inventory visibility, planogram compliance, competitor analysis, promotional campaigns, and quality control.
The significance of this approach amplifies when expanding image recognition capabilities across diverse catalogues and retail locations. Recognising that the efficacy of image recognition, whether synthetic or traditional, hinges on the quality of its data, synthetic data emerges as the rising star. Fuelled by the reasons and benefits outlined above, synthetic data is swiftly becoming the preferred choice, outshining its real-world counterpart.
Technology
When it comes to image recognition, traditional methods face numerous challenges. Among the most common is the vast amounts of real-world data necessary to sufficiently train algorithms. This process is both time-consuming and costly due to the requirements of data collection and annotation. Compounding this, traditional methods often struggle with a lack of data diversity, limiting the range of scenarios the algorithm can effectively learn. This limitation contrasts sharply with the diverse scenarios encountered in the real world. As a result, traditional IR acts as a bottleneck, needlessly hindering the operations of CPGs.
Introducing Neurolabs’ ZIA
Our cutting-edge synthetic image recognition technology, ZIA standing for Zero Image Annotations, is at the forefront of innovation. Using 3D assets of CPG products and virtual scenes, ZIA delivers product detection and in-shelf insights faster, more accurately, and at a lower cost than any other solution available.
The capabilities of ZIA include:
- Annotation IndependenceZIA eliminates the need for laborious manual image annotations, saving time and money while streamlining the recognition process.
- Cost-Effective ScalingUsers can effortlessly scale operations with ZIA, ensuring a cost-effective and efficient pathway to growth.
- Rapid Onboarding:ZIA offers a remarkable onboarding experience, getting users up and running within a mere 24 hours. You can also onboard SKUs in minutes with our ZIA Capture app.
- Expert SupportWith a dedicated customer support team, ZIA ensures that any challenges are swiftly addressed and resolved within a quick 24-hour turnaround.
- Reliable data and insightsWith ZIA you can achieve a visual detection accuracy rate of +95% from the outset and increase to above 98% for specific categories. You can also access our ChatCPG AI Assistant to extract reliable insights from your data in seconds!
Elevating CPG Operations with SCV
Synthetic Computer Vision (SCV) emerges as the driving force behind operational excellence for Consumer Packaged Goods (CPG). Let's explore the impactful roles it plays:
Product Detection and Classification:
SCV brings automation to the forefront by swiftly and accurately detecting and classifying products on store shelves. This helps CPG brands to ensure that their products are properly displayed and stocked according to the relevant planogram compliance standards. Additionally, SCV's prowess extends to tracking inventory levels with precision, ensuring a seamless and compliant supply chain.
Precision in Deformed Product Detection:
SCV goes above and beyond by showcasing its ability to identify deformed products, a particularly invaluable feature when auditing items with soft packaging like crisps or frozen produce. The accuracy of SCV shines through, contributing to a more precise and reliable product inspection and data collection process.
Precision in Stock Level Estimation:
Transforming inventory management, SCV empowers CPG brands with accurate stock level estimations, proactively preventing Out-of-Stock (OOS) and dead stock scenarios. This ensures well-informed stocking decisions, mitigating the risks associated with costly stock-related mistakes.
Strategic Backroom to Storefront Integration:
In the intricate dance of inventory, SCV acts as a linchpin, enhancing the connection between the backroom and storefront through real-time tracking of inventory levels. This dynamic feature ensures a constant flow of stock to the shelves, minimising the likelihood of out-of-stock situations and enhancing overall operational efficiency.
Strategic Analysis of POP Displays and Signage:
SCV takes centre stage in meticulously analysing Point-of-Purchase (POP) Displays and Signage, ensuring a flawless presentation of products within the store. This meticulous attention to detail becomes a cornerstone for an enhanced customer experience and a direct contributor to revenue growth.
Elevating Customer Experience in Competitive Categories:
In fiercely competitive sectors like FMCG, Home Appliances, Telecom, and Electronics, SCV becomes a crucial ally, delivering those marginal gains indispensable for effective competition. By ensuring products are accurately displayed, SCV not only improves the overall customer experience but also strategically boosts revenue in these highly contested categories.
Efficient Algorithm Training:
SCV doesn't just offer speed but efficiency in training algorithms, translating to faster and more cost-effective scaling. This implies substantial growth with reduced investment, making SCV a strategic choice for businesses aiming to expand their operations.
Proactive Training Ahead of Shelves:
A game-changer in time-sensitive scenarios, SCV can be trained before products hit the shelves, requiring only the artwork. This guarantees swift detection and provides accurate insights, as the technology is pre-equipped with knowledge about the promoted products, ideal for POP campaigns and trade promotions with shorter lead times.
Direct Impact on Operational Scale:
We've witnessed firsthand the transformative power of SCV in action. By assisting one of our partners, a global beverage CPG, in scaling their operations, we cut down the implementation time from over 6 months with traditional methods to a mere 2 months. Moreover, the results spoke volumes, delivering significant ROI at a fraction of the cost. It's a testament to the real and substantial impact SCV can have on business growth.
Elevate Your Retail Shelf Auditing with Synthetic Computer Vision
The adoption of synthetic computer vision is now indispensable for achieving effective retail execution. CPGs that fail to adapt risk falling behind in the current competitive landscape and compromising their future success.
To ensure you stay ahead of your competitors, book your demo today.
At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.
