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Seabed.AI
London, United Kingdom
1-10 Employees
2020
We provide a quick assessment of the field and identify key obstacles (e.g. Seabed survey providers can save months of their time by using the AI engine for pre-processing of SSS mosaics. Seabed survey supervisors, responsible for the quality check can benefit from the automated review of the survey. Seabed.AI results can potentially shorten the contact identification cycle during marine surveys significantly. Seabed.AI is a British company founded by experts in offshore projects, AI and technology. Seabed.AI picking and sizing objects artificial intelligence engine reduced marine survey processing time from months to days. Unlike human experts, an AI engine can analyse all data to see if any SSS images contain suspicious abnormalities, overlooked in the current report. With our tool, the quality supervisor can focus on the problem areas rather than repeat the surveyor's work.
Core business
Seabed.AI – AI-enabled quick and reliable seabed side-scan sonar object detection
... I – AI-enabled quick and reliable seabed side-scan sonar object detection ...
RED DOT DRONE
San Jose, Philippines
1-10 Employees
2017
Our service consists of useful tools to manage all drone operation phases; before, during, and after flight. Red Dot Drone is a drone software company. DWS provides edge & cloud tools to manage your drone operations safely with ease. DroneMQTT is a message broker hosting service for drones implementing the MQTT protocol.
Product
Object Detection
... Object detection for drone control and ...
Einstein
San Francisco, United States
- Employees
-
We’re researching and developing AI to create breakthrough technologies for our company, our customers, and the world. As an Executive Vice President and Chief Scientist of Salesforce Research, Silvio plays a key role in ensuring AI research and technology leadership, setting medium and long-term strategy, and influencing scientific investments. As COO, Vanita owns and drives the cadence of the organization by partnering with the Chief Scientist and leadership to define the vision, strategy and execution plan. She leads and drives execution and operations to support innovation and deliver AI to the Salesforce suite of products. As a VP/managing director of AI Research at Salesforce, Caiming leads to build the state-of-the-art AI technologies, publish in top academic conferences, innovate, collaborate and embed our work across Salesforce clouds to accelerate the building of AI products.
Product
Einstein Object Detection
... Einstein Object Detection | Salesforce ...
Andium
New York, United States
11-50 Employees
2013
Andium has transformed wellsite management for the oil and gas industry. Discover how Andium's innovative solutions deliver accurate and actionable information in real time. Andium technology gives you a clear path to achieving your net-zero emissions goals. The world’s leading energy producers rely on our innovations to reach their emissions goals. Companies keep their operations safe, sustainable, and profitable with Andium's insights and visibility. Reducing fugitive emissions is critical to reversing climate change. Most importantly, our clients have stayed committed to their Net-Zero promises.
Product
Advanced Object Detection
... Andium Advanced Object Detection / Andium | See ...
Matrix AI
Sydney, Australia
1-10 Employees
2014
We provide Machine Learning services across all industries. Matrix AI is a Sydney based company that provides end to end machine learning application development services. We deliver full stack software solutions to automate your business processes. Matrix, our core product which is an operating system designed for the next era of cloud, machine-learning and internet of things. We are experts at deploying machine-learning infrastructure at scale. Founded in Sydney, Australia on August 2014, Matrix OS was created to make DevOps and Software Deployment Automation tools more user-friendly for software developers. From 2016 to 2019 we formed a team to build Matrix OS, our core product. Our past and current clients operate in energy, mining, and documentation processing.
Service
Object Detection
... on Image Classification, Object Detection, Image Segmentation, and ...
Edgeble AI
Hyderabad, India
1-10 Employees
2022
Edgeble AI is an Artificial Intelligence company with a focus on deploying Neural Acceleration principles at the Edge. We are a group of technology and business leader whose products and services are already impacted many people and companies across the globe. Our mission is to deploy high-performance, neurally fast AI Accelerators using state-of-the-art Pre-trained AI Accelerator Platform for Edge AIoT-enabled solutions in consumer, industrial, and automotive markets. Edgeble has engineered an OpenAIA platform stack that will accelerate the time-to-market for a world of companies that are producing high-grade Edge AI-enabled solutions. Performace-driven standardized compute modules with built-in Neural Engines that are ready to deploy in any AIoT sector. State-of-the-art pre-trained model conversion delivers a single API to develop AI applications. A Comprehensive Pre-trained AI Accelerator Platform deliver AI Accelerators with one platform looped on end-to-end devops.
Product
Object detection
... Object detection ...
RAPT Touch
Dublin, Ireland
11-50 Employees
2011
RAPT is the leading provider of alternative multi-touch systems for Global Consumer OEMs and Systems Integrators. For high volume consumer applications, material and manufacturing cost optimization requires specific integration into your product.RAPT’s team of optical, electrical, firmware and mechanical engineers tailor a qualified platform to adapt to your specific requirements. RAPT’s custom design delivers:Prototype pilot buildsEngineering verificationDesign validationProcess verification cyclesManufacturing test systems. For device manufacturers, RAPT includes the tools and resources to quickly and cost effectively commercialize a device:including access to hardware components which have been tested against various RAPTs designs and deliver the features and capabilities that cater to todays demanding consumers. RAPT enables tier-one partners with all of the designs necessary to manufacture RAPT systems. RAPT’s qualified manufacturing partners provide:Cover glass finishingInjection moldingLamination on cover glassElectronics. RAPT is the leading provider of optical multi-touch systems for Global Consumer OEMs and Systems Integrators. For high volume consumer applications, material and manufacturing cost optimization requires specific integration into your product.
Product
Object Detection?
... Object Detection? ...
Neonode
Stockholm, Sweden
51-100 Employees
2001
Neonode has a long history of innovation of advanced, multi-modal human-machine interaction (HMI) solutions. We are the go-to company for Touchless Interaction, Object Detection, Infrared Touch and Machine Perception. To date, Neonode’s proven technology is deployed in more than 90 million products around the world. At Neonode we transform the way humans and machines interact. As an employee at Neonode we promise you a workplace that invests in your career, cares for you and is highly creative and engaging. As an employee at Neonode, we promise you a workplace that invests in your career, cares for you and is highly creative and engaging. Neonode has been found to conform to the Quality Management System standards ISO 9001:2015 and ISO/IEC 27001:2013. Customers come to Neonode for cutting edge technological solutions that hold up in tough environments and that deliver results which drive businesses forward.
Product
Object Detection
... Object detection using infrared sensing that recognizes foreign objects ...
SmartSurv Vision Systems GmbH
Sindelfingen, Germany
1-10 Employees
2007
Die SmartSurv Vision Systems GmbH hat als für die Verarbeitung Verantwortlicher zahlreiche technische und organisatorische Maßnahmen umgesetzt, um einen möglichst lückenlosen Schutz der über diese Internetseite verarbeiteten personenbezogenen Daten sicherzustellen. Die Datenschutzerklärung der SmartSurv Vision Systems GmbH beruht auf den Begrifflichkeiten, die durch den Europäischen Richtlinien- und Verordnungsgeber beim Erlass der Datenschutz-Grundverordnung (DS-GVO) verwendet wurden. Die Internetseite der SmartSurv Vision Systems GmbH erfasst mit jedem Aufruf der Internetseite durch eine betroffene Person oder ein automatisiertes System eine Reihe von allgemeinen Daten und Informationen. Die Internetseite der SmartSurv Vision Systems GmbH enthält aufgrund von gesetzlichen Vorschriften Angaben, die eine schnelle elektronische Kontaktaufnahme zu unserem Unternehmen sowie eine unmittelbare Kommunikation mit uns ermöglichen, was ebenfalls eine allgemeine Adresse der sogenannten elektronischen Post (E-Mail-Adresse) umfasst. Der Mitarbeiter der SmartSurv Vision Systems GmbH wird veranlassen, dass dem Löschverlangen unverzüglich nachgekommen wird. Der Mitarbeiter der SmartSurv Vision Systems GmbH wird im Einzelfall das Notwendige veranlassen. Der Mitarbeiter der SmartSurv Vision Systems GmbH wird die Einschränkung der Verarbeitung veranlassen. Die SmartSurv Vision Systems GmbH verarbeitet die personenbezogenen Daten im Falle des Widerspruchs nicht mehr, es sei denn, wir können zwingende schutzwürdige Gründe für die Verarbeitung nachweisen, die den Interessen, Rechten und Freiheiten der betroffenen Person überwiegen, oder die Verarbeitung dient der Geltendmachung, Ausübung oder Verteidigung von Rechtsansprüchen.
Core business
Metrics for Image Quality, Calibration, Object Detection/Classification.
... Metrics for Image Quality, Calibration, Object Detection/Classification. ...
Amelue Technologies
North Vancouver, Canada
1-10 Employees
2017
Further, we are experts at incorporating strategies into UI/UX for data collection suitable for analysis using artificial intelligence. We offer solutions ranging from simple web-pages all the way to tailor-made mobile apps (both iPhone and Android) having cloud-based back-ends and incorporating the latest in deep-learning based artificial intelligence. We offer deep learning based solutions in computer vision (including object detection and semantic segmentation), natural language processing, and data analysis. We specialize in hand-drawn, hand-painted and hand-lettered elements. We offer deep learning based solutions in computer vision, natural language processing and data analysis. Make your next project a reality with Amelue!
Core business
State of the Art Object Detection & semantic segmentation
... State of the Art Object Detection & semantic ...
Technologies which have been searched by others and may be interesting for you:
Some interesting numbers and facts about your company results for Object Detection
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 2128 |
| Amount of suitable service providers | 1110 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 2003 |
| Youngest suiting company | 2020 |
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Object Detection is a computer vision technique that identifies and locates objects within digital images or videos. This involves not only classifying the objects seen (answering the question, "What is this object?") but also precisely outlining their presence within the image through bounding boxes or segmentation masks. Object detection algorithms leverage machine learning or deep learning models trained on vast datasets of labeled images to recognize various objects. These models learn to extract features from images that are indicative of particular objects, enabling them to distinguish between different object types and their instances in unseen images. The impact of object detection spans across numerous industries and applications, significantly transforming how machines interact with their environments. In the automotive industry, it powers advanced driver-assistance systems (ADAS) for identifying pedestrians, vehicles, and road signs, enhancing safety and paving the way for autonomous driving. In retail, it facilitates inventory management and checkout processes by recognizing products without the need for barcodes. Additionally, in security and surveillance, object detection aids in monitoring areas for unusual activities or identifying items of interest in crowded scenes. The technology's ability to provide detailed analyses of visual data in real-time or from recorded footage marks a pivotal advancement in making machines more intelligent and responsive to the physical world, thereby revolutionizing a broad spectrum of sectors with its application.
1. Real-Time Processing
Object detection technologies excel in their ability to process and analyze visual data in real time. Unlike traditional methods which may require manual input or slower analysis, object detection systems can instantly identify and classify various objects within images or videos. This capability is crucial for applications requiring immediate response, such as autonomous driving or security surveillance.
2. Accuracy and Reliability
Thanks to advancements in artificial intelligence and machine learning, object detection algorithms have reached unprecedented levels of accuracy. They significantly reduce the margin of error compared to human analysis, especially in complex or cluttered scenes where manual identification can be challenging or subjective. This reliability supports critical applications in areas like medical imaging, where precise detection can have profound implications.
3. Scalability
Object detection systems are inherently scalable, capable of handling an increasing number of objects or scenarios without a substantial increase in effort or resources. This scalability contrasts with traditional manual methods, which become exponentially more resource-intensive as the volume of data grows. As a result, object detection is ideal for large-scale applications, from city-wide surveillance systems to analyzing extensive image databases for research.
4. Automated Data Extraction
By automating the process of identifying and categorizing objects within images, object detection enables efficient data extraction. This automation not only saves time but also unlocks new possibilities for data analysis and utilization, paving the way for innovations in fields like retail analytics, where understanding customer interactions with products can lead to enhanced shopping experiences.
1. Accuracy and Reliability
Ensure the supplier's technology consistently delivers high accuracy in object detection across various conditions and environments. This factor is crucial for applications requiring precise identification and classification.
2. Speed and Efficiency
Evaluate the processing speed of the object detection system. It should be capable of real-time detection to suit applications that demand immediate responses, such as autonomous driving or security surveillance.
3. Scalability
Consider if the supplier’s solution can scale according to your needs. This includes the ability to handle increasing volumes of data or the capability to upgrade as technology advances.
4. Integration Capability
Assess how easily the object detection system can be integrated with existing infrastructure. Compatibility with current systems and software can significantly reduce implementation time and costs.
5. Customization
Determine if the supplier offers customization options. Tailoring the object detection system to specific requirements can enhance its effectiveness and efficiency in particular applications.
6. Support and Maintenance
Look into the supplier's support and maintenance services. Reliable technical support and regular updates are essential to ensure the long-term viability of the system.
Object detection technology is revolutionizing the retail industry by enabling automated inventory management. Through sophisticated algorithms, cameras can identify and track products on shelves in real time, significantly reducing the manual labor involved in stocktaking and replenishment processes. This automation not only streamlines operations but also enhances accuracy in inventory control, leading to improved customer satisfaction through better stock availability. In the manufacturing sector, object detection plays a crucial role in quality control. By integrating this technology into production lines, companies can automatically inspect products for defects or inconsistencies. This real-time detection allows for immediate corrective actions, minimizing waste and ensuring that only products meeting the strictest quality standards reach the market. The result is a more efficient production process and a higher quality product offering. The transportation and logistics industry benefits from object detection through enhanced safety and security measures. By employing this technology in surveillance systems, companies can monitor cargo and detect unauthorized access or tampering. Additionally, object detection can be used in fleet management to identify obstacles or hazards on the road, significantly reducing the risk of accidents. This proactive approach to safety and security not only protects assets but also ensures the well-being of employees and the public.
Object detection technology, pivotal in various fields like autonomous vehicles, security, and retail analytics, currently stands at a high Technology Readiness Level (TRL) of 8 to 9. This status is attributed to its extensive validation in real-world environments and its integration into operational systems. The advancement to such a mature stage is primarily due to significant breakthroughs in deep learning and computer vision over the past decade. Convolutional Neural Networks (CNNs), for instance, have drastically improved the accuracy of object detection by enabling systems to learn and identify objects from vast datasets with minimal human intervention. Furthermore, the availability of large annotated datasets and powerful computational resources has accelerated the development and refinement of algorithms, making them more robust to variations in object size, shape, and environmental conditions. The continual evolution of edge computing devices also supports the high TRL by facilitating faster, local processing of object detection tasks, reducing latency, and enhancing the applicability of technology in time-sensitive scenarios. However, challenges such as detecting objects in highly cluttered scenes or under poor lighting conditions continue to be areas of active research, indicating that while the technology is mature, there is ongoing development to push its boundaries further.
In the Short-Term, advancements in object detection technologies are expected to focus on improving accuracy and speed. Enhanced algorithms will likely reduce false positives, making object detection more reliable for applications such as autonomous vehicles and surveillance. Integration with edge computing will also become more prevalent, enabling faster processing times by decentralizing data analysis, which is critical for real-time applications. The Mid-Term phase will likely witness the incorporation of more sophisticated artificial intelligence (AI) models that can understand contextual information, leading to a significant improvement in object detection capabilities. These models will be better at distinguishing between objects in complex environments, such as crowded urban areas. Additionally, advancements in sensor technology will provide higher resolution images, further boosting the accuracy of object detection systems. This period will also see the beginning of widespread adoption in industries such as retail, for inventory management, and in healthcare, for patient monitoring. In the Long-Term, object detection technology is expected to evolve to a point where it can predict future movements and interactions of detected objects. This predictive capability will be powered by advanced machine learning algorithms analyzing vast datasets to understand patterns and behaviors. Such advancements could revolutionize fields like urban planning and traffic management, providing unprecedented levels of efficiency and safety. The integration of object detection with augmented reality (AR) and virtual reality (VR) could also create immersive experiences that blend the real and digital worlds seamlessly.
Some interesting questions that has been asked about the results you have just received for Object Detection
What are related technologies to Object Detection?
Based on our calculations related technologies to Object Detection are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Who are Start-Ups in the field of Object Detection?
Start-Ups who are working in Object Detection are RapidAI Vision, WENODE
Which industries are mostly working on Object Detection?
The most represented industries which are working in Object Detection are IT, Software and Services, Other, Automation, Defense, Electronics and Electrical engineering
How does ensun find these Object Detection Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
