Video Object Recognition

Science and Research

Fennaio | artificial intelligence software

Video Object Recognition AI Software for the Science and Research industry


Artificial Intelligence Software
Machine Learning Data Science Software
Deep Learning Software

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We are specialists in the practical application of Artificial Intelligence including Video Object Recognition AI, Machine Learning, Deep Learning and Data Science Software used within Science and Research processes and operations

AI can accurately and rapidly recognise objects in moving images/videos whether it's a bird, plane, human or something incredibly small.

The power of video object recognition

Being able to automatically recognise patterns, shapes, sizes, colours and orientation of objects within moving images or videos is an extremely powerful tool in a wide range of businesses, operations, tasks and processes.

By learning from known and highly variable image shapes, textures, dimensions, movements, behaviours, positions in space (2D/3D) including all the in-between highly variable and unpredictable moving object attributes; video object recognition becomes more insightful, more meaningful, more accurate and much more beneficial when used for tasks and processes like: e.g. object classification, automatic and rapid video-based diagnosis, anomaly detection, quality control, computer vision, behavioural analysis, investigations, self-driving vehicles, threat assessment, robotics, security, and responding to visual changes in any type of dynamic, moving environment, amongst many more cases.

The accuracy of video object recognition is directly proportional to what is already known about certain objects (e.g. their full range of attributes, dimensions and movement dynamics): the more past images and objects to learn from the more accurate and informed we can conduct future video object recognition.

NameELDR-I Video
AI EngineELDR-I
Release DateApril 2021
Version1.0
Hosting/installationLocal Standalone, Internal Network or Cloud
IntegrationDirect coupling or RESTful API
PriceContact Us
LicenceContract basis
SLAContract basis
UpgradesContract basis

Artificial Intelligence makes automatic video object recognition highly dynamic and incredibly accurate

Learning from past images in order to recognise the same type of image/object in a video or moving image in the future might sound straightforward - it is of course exactly what a human brain does all the time - but making this process automatic and asking a machine to do this is extremely complex and demanding, mainly due to the huge amount of variability involved: size, shape, orientation, movements in space, perspective, direction, distance, colour and lighting - and these are variations that can happen for just one object, let alone when you have multiple types of object in the same video.

If a traditional software programming approach was used, the computer would continually be asking "if this, then learn that; if x and y, learn z". This stepwise methodology is extremely tedious, inefficient and resource-heavy as the program will only do what it has explicitly been told to look for by the programmer; making it next to impossible to account for all possibilities and variations, even in the simplest of videos frames. You certainly couldn't use this approach for complex and diverse scenarios e.g. multiple objects in the same video, or indeed where a single object within an video frame showed more than a couple of variations, unlike most objects that contain many hundreds, if not thousands of variable attributes.

With AI and Machine Learning technology it is now possible to learn from near infinite amounts of variable, constantly changing image and object data in order to carry out much more accurate and rapid video object recognition, automatically.

ELDR-I Video is a powerful Deep Learning Video Object Recognition package that can accurately and rapidly help recognise unlimited images/objects within moving images and videos based on variable past and complex image data it has learnt from

ELDR-I Video is built around our powerful ELDR-I AI Engine, which is a Deep Learning Convolutional Neural Network and is a variant of our ELDR-I Image Recognition software. ELDR-I Video uses Supervised Learning and Image Classification to learn how to recognise all types of images and objects thrown at it, regardless of size, complexity and granular detail (down to the single pixel level).

When ELDR-I Video has learnt (trained) from the data, it is then primed to receive current-status image/video frame data in real time from which to rapidly process moving frames and recognise/classify objects within - in order to give a response - and that response can range from a simple classification to a "yes/no" to triggering sophisticated downstream events, or marking a particular object on the moving image or video itself.

ELDR-I Video is highly dynamic, autonomous, configurable, graphical and easily integrated

Dynamic

ELDR-I Video can handle and learn from multiple sources, sizes and complexities of image object data for numerous environments and requirements simultaneously. Data can be changed at any time and it can continually learn.

Autonomous

By default ELDR-I Video is plug and play - you can simply give it appropriately formatted image object data and it will automatically learn from it, including self optimisation, self scaling and classification.

Configurable

In some cases you may be happy with plug and play, however almost everything in ELDR-I Video is configurable; from labelling of images, to colours, displays, output format, learning modes, learning accuracy, all the way through to Convolutional Neural Network dynamics and dimensions.

Graphical

ELDR-I Video uses a rich intuitive GUI Dashboard from which to manage the whole AI process (image object data preparation, learning, outputting and testing), including a comprehensive suite of gamified charts and other visual displays to monitor everything.

Easily Integrated

AI Integration is our speciality. We understand that AI can be used in a variety of ways and in numerous system-types and processes. We build our software to be entirely modular and there are multiple integration methods and points ranging from network-based RESTful API integration to direct coupling at the code level, depending on the response time required, amongst other considerations.

Key points about our Video Object Recognition AI software

  • Can help recognise images and objects within moving images/objects to high degree of accuracy, after learning from past image object data
  • Can handle numerous data streams and outputs simultaneously
  • Uses our powerful ELDR-I AI Deep Learning Convolutional Neural Network Engine
  • Dynamic
  • Autonomous
  • Configurable
  • Graphical
  • Easily Integrated

Example areas where Fennaio can help with AI, Machine Learning and Deep Learning in the Science and Research industry


AI can be used all over the Science and Research industry, including these processes, operations and tasks:
  • data analysis
  • predictions
  • modelling
  • big data
  • high throughput analysis
  • experimental design
  • simulations
  • genomic analysis
  • proteomic structure
  • molecular interactions
  • discovery
  • data science
  • diagnostics
  • image recognition
  • microscopy
  • object and video recognition
  • reaction dynamics
  • theory robustness
  • data visualisation
  • literature review
  • data harvesting
  • data optimisation
  • data filtering
  • cross study data relationships
  • many more...

How Fennaio can help you efficiently integrate Video Object Recognition AI Software with your Science and Research operations


AI Education

for Video Object Recognition in the Science and Research industry
Fennaio helps your Science and Research organisation with understanding the fundamentals of exactly what Video Object Recognition AI is, how you can use it, where you can use it and how you can implement and integrate it - all in an easy-to-digest manner.

AI Strategy

for Video Object Recognition in the Science and Research industry
Fennaio works closely with you and your relevant teams to understand your Science and Research organisation operations and your long term goals so we can plan when and where to introduce Video Object Recognition Artificial Intelligence with minimum disruption and maximum benefit.

AI Tooling & Development

for Video Object Recognition in the Science and Research industry
Fennaio provides all the relevant hardware, software, network and infrastructure requirements you need to implement Video Object Recognition Artificial Intelligence, whether this be an off-the-shelf software product or system, or a completely bespoke solution, a standalone piece of software or an enterprise-grade package.

AI Data Analytics

for Video Object Recognition in the Science and Research industry
Fennaio partners with you to fully understand your current data, how it relates to and is currently gathered from your current Science and Research operations, and how to harvest, analyse and prepare it for use in Video Object Recognition Artificial Intelligence and Machine Learning to result in maximum gain.

AI Learning

for Video Object Recognition in the Science and Research industry
Fennaio will use your correctly formatted data streams to train the Video Object Recognition AI, Machine Learning or Deep Learning system by using an optimisation and scaling up procedure until the Video Object Recognition AI is fully and continually primed to start outputting useful information for your Science and Research operations.

AI Visualisation

for Video Object Recognition in the Science and Research industry
When the Video Object Recognition AI is fully trained, Fennaio will feed it live Science and Research operations or test data and use various visualisation techniques to confirm with you a beneficial output is being achieved; whether this be a prediction, pattern recognition, a rapid analysis, a diagnosis or any other type of output.

AI Integration

for Video Object Recognition in the Science and Research industry
When you are satisfied the Video Object Recognition AI software is producing effective results, we will integrate the AI into your existing systems if required. Whether this be at the code level, integration over a network or as a standalone process, we will seamlessly integrate the AI with your Science and Research operations.

AI Delivery

for Video Object Recognition in the Science and Research industry
After the Video Object Recognition AI is successfully integrated into your Science and Research operations, we will continue to monitor the whole Video Object Recognition AI process from data acquisition, analysis, processing, learning, visualisation and output until you are fully satisfied you have an AI system that is achieving your operational goals.

Other AI Software for the Science and Research industry

As well as Video Object Recognition software for the Science and Research industry, we provide a comprehensive set of other Artificial Intelligence, Machine Learning, Deep Learning and Data Science software:

How Fennaio works with you at every stage of the AI and ML Integration process.

Whether you are starting out on your first AI project, just interested in the possibilities of AI or are wanting to expand your existing AI suite, we are here to help.

AI Survey & Plan

We will discuss with you where you are, where you want to be, and how we can achieve it with AI - whether by a bespoke solution or using one of our off-the-shelf products

AI Data Analysis & Preparation

We will work with you to gather, analyse and prepare all your relevant data sources for use in the AI system(s)

AI Execute & Visualisation

We will run and tune the AI throughout the AI learning process and enable the AI to produce a real time visual output to confirm the AI is producing beneficial results

AI Integration

When you are satisfied the AI is delivering the results you desire, we will integrate the AI with your new or existing systems

You are one step closer to getting Artificial Intelligence into your Science and Research organisation

Fennaio has the expertise in the Science and Research sector to get you up and running with Video Object Recognition AI and Machine Learning in your new or existing systems, software and operations.

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