Industry News
Top 5 Open Source AI Solutions for Image Processing
A few decades or even years ago, self-driving cars and computers with a human-like vision were just a figment of the fantasy writer’s imagination. But today, Artificial intelligence (AI) technologies allow cars to drive safely across busy streets and computers to interpret pictures almost like humans do.
Developers have made impressive progress on how to implement AI on image processing tasks. Furthermore, image processing solutions with AI are widely used in various fields, from medicine to law enforcement to cybersecurity and retail.
AI and machine learning make it possible for the machines to inherit new functionalities through the process of learning. Similarly to small kids, machines can gain the ability to acquire and understand visual information by processing massive amounts of images. To process so much data faster without compromising the final result, developers use image processing models based on machine learning and deep learning algorithms.
In particular, image processing and computer vision solutions use deep learning for accomplishing such complex tasks as:
- Image classification
- Object recognition
- Object tracking
- Image generation
- Image retrieval
To implement some computer vision functionalities into your product, you’ll need a large set of tools and resources: image datasets, libraries with code samples, frameworks for creating and training deep learning models. Fortunately, there are a lot of open-course services that you can use to make machine learning less of a mystery and ease the development of your own AI-based image processing solution.
Below, we take a closer look at the five best open source image processing solutions that you can apply to your projects:
- OpenCV
- TensorFlow
- Keras
- Caffe
- Google Colab
Let’s get started!
OpenCV
Open Source Computer Vision Library (OpenCV) is one of the most popular open source services for image processing. It’s a free computer vision library that you can use to perform various image processing tasks:
- Image acquisition
- Image compression and decompression
- Image enhancement and restoration
- Image denoising
- Image segmentation
- Data extraction, and more
The library includes numerous algorithms and functions as well as special modules aimed at image processing tasks. Starting from the library version 3.1, there’s also a deep learning module for building and training deep learning models.
With this module, you can use OpenCV to extract features from processed images, and then apply a machine learning model using one of the supported machine learning frameworks.
As of today, OpenCV supports a number of popular frameworks, including TensorFlow, PyTorch, and Caffe. The list of supported types of neural networks includes convolutional, deconvolutional, and recurrent neural networks.
The library is written in C++ and supports C++, Java, Python, and MATLAB interfaces.
TensorFlow
TensorFlow is an open-source machine learning framework created by Google. Initially, the project was started for research purposes of the Google Brain team. Today, however, TensorFlow is widely used by both small startups and large companies such as Dropbox, Intel, and Twitter.
You can use TensorFlow to process different types of data, but in relation to image processing, this framework works best for:
- Image classification
- Image recognition
- Image segmentation
- Image to image translation (pix2pix)
TensorFlow includes a set of libraries for creating and training custom deep learning models and neural networks. The framework supports Jupyter notebooks and provides a style guide with recommendations on writing readable, consistent code.
TensorFlow supports several popular programming languages, including C++, Python, Java, Rust, and Go. However, you can install third-party bindings for other languages, such as Ruby, Scala, or PHP.
Keras
Keras is an open-source Python library for creating deep learning models. It’s a great solution for those who only begin to use machine learning algorithms in their projects as it simplifies the creation of a deep learning model from scratch. Keras is easy to manage and it is suitable for fast and simple prototyping of different types of neural networks.
The library was built on TensorFlow and is currently fully integrated into the framework. This means that you can write your deep learning model in Keras, as it has a much more user-friendly interface, and then easily implement a specific functionality or feature from TensorFlow in this model.
Keras can also be deployed on top of other popular AI frameworks such as Microsoft Cognitive Toolkit and Theano.
Caffe
Convolutional Architecture for Fast Feature Embedding (Caffe) is an open-source framework that can also be used for creating and training popular types of deep learning architectures. You can use Caffe to accomplish such tasks as image classification, segmentation, and recognition.
Caffe is written in C++ but it also has a Python interface. The framework supports both CPU- and GPU-based accelerated libraries such as NVIDIA cuDNN and Intel MKL. The framework also has a special database, Caffe Model Zoo, containing a set of pre-trained deep learning models. As of today, it offers four BAIR-trained models:
- BAIR Reference CaffeNet
- BAIR Reference R-CNN ILSVRC-2013
- BAIR AlexNet
- BAIR GoogLeNet
Model Zoo also includes a number of community models trained by other Caffe users. As for the types of supported neural networks, Caffe works best with convolutional neural networks (CNN) and feedforward networks. At the same time, it’s not the best choice for training recurrent neural networks.
In 2017, Facebook launched Caffe2, an open-source framework for training and deploying deep learning models. And in 2018, Caffe2 was integrated with another popular AI framework, PyTorch.
Caffe2 comes with C++ and Python APIs and supports all popular platforms.
Google Colaboratory (Colab)
Google Colaboratory, or simply Colab, is one of the top image processing services. While it’s rather a cloud service than a framework, you can still use Colab for building custom deep learning applications from scratch. With the help of Colab, you can perform such image processing tasks as image classification, segmentation, and object detection.
Google Colab eases the use of other popular AI-based tools such as OpenCV, TensorFlow, and Keras. The service uses Jupyter Notebooks, helping developers to share their knowledge, tips, and best practices on building AI-based applications. Plus, in contrast to other similar services, Colab offers free usage of both CPU- and GPU-based acceleration.
Conclusion
Machine learning models and algorithms help developers implement specific image processing functionalities into their products both quickly and easily. However, building a custom machine learning model or neural network requires lots of resources and a high level of technology expertise. With the help of the listed open-source tools, libraries, and frameworks, you can simplify the process of leveraging Artificial Intelligence technologies to your benefit.
This article is a contribution from Marcell Gogan. Marcell is a specialist within digital security solutions, business design and development, virtualization and cloud computing, R&D projects, establishment and management of software research direction – working with Ekran System. He also loves writing about data management and cybersecurity.
Industry News
Europe Sports Betting Market Size, Share & Trends Analysis Report 2024-2030 Featuring Bet365, William Hill, Betfair, Paddy Power, 888sport, Bwin, Unibet, Ladbrokes, MGM, and Betsson
The “Europe Sports Betting Market Size, Share & Trends Analysis Report by Type, Platform, Sports Type (Football, Basketball, Baseball, Horse Racing, Cricket, Hockey, Others), Country, and Segment Forecasts, 2024-2030” report has been added to ResearchAndMarkets.com’s offering.
The Europe sports betting market size is anticipated to reach USD 65.54 billion by 2030 and is expected to expand at a CAGR of 9.9% from 2024 to 2030
The globalization of sports and the integration of international leagues and tournaments into European betting markets have fueled the growth of sports betting. Major sporting events such as the FIFA World Cup, UEFA European Championship, Wimbledon, and the Olympics attract widespread attention and betting interest from European consumers, driving significant betting volumes and revenues for sports betting operators, thus driving the growth of the sports betting market in Europe.
The COVID-19 pandemic had a negative impact on the European sports betting market. The cancellation or postponement of sports events during the pandemic restrained the market growth. With major tournaments, leagues, and competitions either suspended or canceled outright, the absence of live sports events severely diminished consumer betting opportunities. It led to a significant decline in betting volumes and revenues for sports betting operators.
The presence of favorable betting policies in the region is driving the growth of the sports betting market in the region. Many European countries, such as the UK, Ireland, Denmark, and France, have progressive policies promoting a competitive and well-regulated betting market. It facilitates the entry of new operators into the market and encourages competition, leading to innovation, improved services, and better value for consumers.
Moreover, established responsible gambling initiatives and regulatory bodies in Europe, such as the European Gaming & Betting Association, help build trust and confidence among consumers by promoting responsible gambling practices, ensuring fairness and transparency in betting operations, and providing avenues for dispute resolution, to protect consumers and maintain the integrity of the betting market, thus driving the growth of sports betting market in the region.
Europe Sports Betting Market Report Highlights
- Based on the type of betting, the fixed odd wagering segment accounted for the highest revenue share of 27.7% in 2023 due to the stability and predictability of the payouts
- Based on platform, the online segment dominated the market in 2023 and is expected to grow at a significant CAGR from 2024 to 2030. It can be attributed to the collaborations between sports teams, leagues, and betting companies, thus increasing the visibility of sports betting and attracting a larger customer base.
- In terms of sports type, the football segment accounted for the largest revenue share in 2023. It can be attributed to the popularity of football in Europe due to popular football clubs like Real Madrid, Liverpool FC, FC Barcelona, and Manchester United.
- The UK held a significant share of 34.6% in 2023 and is expected to grow at a significant CAGR during the forecast period. Favorable gambling policies in the country drive the market’s growth.
Company Profiles
- Bet365
- Ali William Hill
- Betfair
- Paddy Power
- 888sport
- Bwin
- Unibet
- Ladbrokes
- MGM Resorts International
- Betsson
Key Attributes:
Report Attribute | Details |
No. of Pages | 80 |
Forecast Period | 2023 – 2030 |
Estimated Market Value (USD) in 2023 | $33.75 Billion |
Forecasted Market Value (USD) by 2030 | $65.54 Billion |
Compound Annual Growth Rate | 9.9% |
Regions Covered | Europe |
Key Topics Covered:
Chapter 1. Methodology and Scope
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.3. Competitive Insights
Chapter 3. Europe Sports Betting Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.1.1. Increasing number of sport events
3.2.1.2. Growing number of sporting events and leagues in Europe
3.2.2. Market restraint analysis
3.2.2.1. Lack of unified regulations
3.2.3. Market opportunity analysis
3.2.3.1. Growth in E-sports audience
3.3. Europe Sports Betting Market Analysis Tools
3.3.1. Industry Analysis – Porter’s
3.3.2. PESTEL Analysis
Chapter 4. Europe Sports Betting Market: Platform Estimates & Trend Analysis
4.1. Platform Market Share, 2023 & 2030
4.2. Segment Dashboard
4.3. Europe Sports Betting Market by Platform Outlook
4.4. Market Size & Forecasts and Trend Analyses, 2018 to 2030
4.4.1. Offline
4.4.2. Online
Chapter 5. Europe Sports Betting Market: Type Estimates & Trend Analysis
5.1. Type Market Share, 2023 & 2030
5.2. Segment Dashboard
5.3. Europe Sports Betting Market by Type Outlook
5.4. Market Size & Forecasts and Trend Analyses, 2018 to 2030
5.4.1. Fixed odds wagering
5.4.2. Exchange Betting
5.4.3. Live/In Play Betting
5.4.4. eSports Betting
5.4.5. Others
Chapter 6. Europe Sports Betting Market: Sports Type Estimates & Trend Analysis
6.1. Sports Type Market Share, 2023 & 2030
6.2. Segment Dashboard
6.3. Europe Sports Betting Market by Sports Type Outlook
6.4. Market Size & Forecasts and Trend Analyses, 2018 to 2030
6.4.1. Football
6.4.2. Basketball
6.4.3. Baseball
6.4.4. Horse Racing
6.4.5. Cricket
6.4.6. Hockey
6.4.7. Others
Chapter 7. Europe Sports Betting Market: Regional Estimates & Trend Analysis
7.1. Regional Market Share Analysis, 2023 & 2030
7.2. Regional Market Dashboard
7.3. Regional Market Snapshot
7.4. Market Size, & Forecasts Trend Analysis, 2018 to 2030
7.4.1. UK
7.4.2. Germany
7.4.3. France
7.4.4. Italy
Chapter 8. Competitive Landscape
8.1. Recent Developments & Impact Analysis, By Key Market Participants
8.2. Company/Competition Categorization
8.3. Vendor Landscape
8.3.1. List of key distributors and channel partners
8.3.2. Key customers
8.4. Company Profiles
For more information about this report visit researchandmarkets.com
Industry News
Leading online slot developer announces launch of Snoop’s High Rollers which will go live exclusively with popular crypto sportsbook and casino
Gaming Corps, a publicly listed game development company based in Sweden, has signed a major deal that will see it launch an exclusive slot game in collaboration with rap legend, Snoop Dogg. The game will drop exclusively on Roobet, the online casino where Snoop Dogg is a brand ambassador.
Snoop Dogg needs no introduction. He made his music industry debut when he appeared on Dr Dre’s 1992 album, The Chronic, and has since sold more than 50 million albums worldwide. He’s also made several movie and TV show appearances, making him one of the most iconic artists of all time.
The game is “Snoop’s High Rollers” and allows players to experience what it’s like to live life as a music legend. The soundtrack is inspired by Snoop’s early and later works and the main man has also narrated parts of the game to really bring it to life.
Snoop has also played a part in creating the gameplay, hand-picking mechanics and bonus features to really put his stamp on the game. Roobet has also got in on the action, leading to a unique online slot that will soar to the top of the charts among its players.
Snoop’s High Rollers will make its debut exclusively on Roobet, the crypto casino and sportsbook that has taken the market by storm since its launch in 2019. The casino’s team has put a comprehensive marketing strategy behind the game with plans to use it to drive new customer acquisition at scale.
“It is with much pride that we at Gaming Corps have had the chance to develop a game in close collaboration with Snoop Dogg and Roobet, where we have combined our unique gaming perspective with Snoop Dogg’s unparalleled style and charisma,” Juha Kauppinen, Gaming Corps CEO, said:-
“Our vision is to offer players an experience where music, culture and gaming merge into something extraordinary. Our close collaboration with Roobet has enabled us to do the impossible, namely world-class marketing, game release is planned for 20 of April. We’re thrilled, and discussions are already underway about several game concepts!”
Anthony Brennan, Head of Partnerships at Roobet, added: “Roobet loves pushing the envelope and never flinches at an opportunity to bring iGaming and pop culture together. Snoop loves his game, we love the game, and we’ve been delighted at the experience of building something that feels fresh in an industry full of remixes.
“We can’t say enough nice things about the Gaming Corps team, and we’re excited to hear what the gaming community has to say!”
Industry News
IDnow Bridges the AI-human Divide with New Expert-led Video Verification Solution
IDnow, a leading identity verification provider in Europe, has unveiled VideoIdent Flex, a new version of its expert-led video verification service that blends advanced AI technology with human interaction. The human-based video call solution, supported by AI, has been designed and built to boost customer conversion rates, reduce rising fraud attempts, increase inclusivity, and tackle an array of complex online verification scenarios, while offering a high-end service experience to end customers.
The company’s original expert-led product, VideoIdent, has been a cornerstone in identity verification for over a decade, serving the strictest requirements in highly regulated industries across Europe. VideoIdent Flex, re-engineered specifically for the UK market, represents a significant evolution, addressing the growing challenges of identity fraud, compliance related to Know-Your-Customer (KYC) and Anti-Money Laundering (AML) processes and ensuring fair access and inclusivity in today’s digital world outside of fully automated processes.
As remote identity verification becomes more crucial yet more challenging, VideoIdent Flex combines high-quality live video identity verification with hundreds of trained verification experts, thus ensuring that genuine customers gain equal access to digital services while effectively deterring fraudsters and money mules. Unlike fully automated solutions based on document liveness and biometric liveness features, this human-machine collaboration not only boosts onboarding rates and prevents fraud but also strengthens trust and confidence in both end users and organisations. VideoIdent Flex can also serve as a fallback service in case a fully automated solution fails.
Bertrand Bouteloup, Chief Commercial Officer at IDnow, said: “VideoIdent Flex marks a groundbreaking advancement in identity verification, merging AI-based technology with human intuition. In a landscape of evolving fraud tactics and steady UK bank branch closures, our solution draws on our decade’s worth of video verification experience and fraud insights, empowering UK businesses to maintain a competitive edge by offering a white glove service for VIP onboarding. With its unique combination of KYC-compliant identity verification, real-time fraud prevention solutions, and expert support, VideoIdent Flex is a powerful tool for the UK market.”
Whereas previously firms may have found video identification solutions to be excessive for their compliance requirement or out of reach due to costs, VideoIdent Flex opens up this option by customising checks as required by the respective regulatory bodies in financial services, mobility, telecommunications or gaming, to offer a streamlined solution fit for every industry and geography.
Bouteloup added: “Identity verification is incredibly nuanced; it’s as intricate as we are as human beings. This really compounds the importance of adopting a hybrid approach to identity – capitalising on the dual benefits of advanced technology when combined with human knowledge and awareness of social cues. With bank branches in the UK closing down, especially in the countryside, and interactions becoming more and more digital, our solution offers a means to maintain a human relationship between businesses and their end customers, no matter their age, disability or neurodiversity.
“VideoIdent Flex is designed from the ground up for organisations that cannot depend on a one-size-fits-all approach to ensuring their customers are who they say they are. In a world where fraud is consistently increasing, our video capability paired with our experts adds a powerful layer of security, especially for those businesses and customers that require a face-to-face interaction.”
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