Unite.AI

NOVEMBER 20, 2024

In 2016, as I was beginning my radiology residency, DeepMind's AlphaGo defeated world champion Go player Lee Sedol. AI will further enhance navigation capabilities with locally embedded computer vision and path planning models.

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AI Weekly

MARCH 14, 2024

The rapid advance of technology and its impact on skilled and unskilled workers has hovered over the American landscape since the 2016 presidential election. has introduced “Maternity Warden,” a computer vision monitoring device that monitors close-up dry cows. How Will AI Impact Inequality And Energy?

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Viso.ai

DECEMBER 6, 2024

Computer vision is a key component of self-driving cars. In this article, we’ll elaborate on how computer vision enhances these cars. To accomplish this, they require two key components: machine learning and computer vision. The eyes of the automobile are computer vision models.

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Viso.ai

JANUARY 9, 2024

Computer Vision technology has rapidly advanced in recent years and has become an important technology in various industries such as security , healthcare , agriculture , smart city , industrial manufacturing , automotive , and more. provides the leading end-to-end Computer Vision Platform Viso Suite. About us: Viso.ai

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). In this article, we dive into some of the most significant research papers that triggered the rapid development of computer vision.

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Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. Object detection is a key field in artificial intelligence, allowing computer systems to “see” their environments by detecting objects in visual images or videos.

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Unite.AI

MARCH 5, 2024

Review of Previous YOLO Versions The YOLO (You Only Look Once) family of models has been at the forefront of fast object detection since the original version was published in 2016. The upgrades provide a strong foundation for future innovation in this critical computer vision capability.

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Towards AI

JULY 19, 2023

Photo by Maud CORREA on Unsplash Computer Vision Using Computer Vision Introduction Crack detection is crucial in monitoring the health of infrastructural buildings. Therefore, Now we conquer this problem of detecting the cracks using image processing methods, deep learning algorithms, and Computer Vision.

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Viso.ai

OCTOBER 15, 2024

In the following, we will cover the following: Pose Estimation in Computer Vision What is OpenPose? provides the leading Computer Vision Platform, Viso Suite. Global organizations use it to develop, deploy, and scale all computer vision applications in one place. How does it work? How to Use OpenPose?

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Convolutional Neural Networks Computer Vision Neural Network Algorithm 98

Unite.AI

JULY 24, 2023

Ever since its launch, the YOLOv7 has been the hottest topic in the Computer Vision developer community, and for the right reasons. What makes YOLOv7 so efficient in performing computer vision tasks? Object detection is a branch in computer vision that identifies and locates objects in an image, or a video file.

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Algorithm Computer Vision Explainability Neural Network 130

Marktechpost

NOVEMBER 18, 2023

In Australia’s Great Barrier Reef in 2016, bleaching killed 29–50% of the coral. Due to artifacts and ambient noise in the underwater picture, the computer vision system finds it challenging to discriminate between the target item in the foreground and the background.

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Machine Learning Neural Network Computer Vision Deep Learning 111

PyImageSearch

NOVEMBER 13, 2023

2015 ; Redmon and Farhad, 2016 ), and others. 2016 ), or a smaller, more compact network for resource-contained devices (e.g., Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? 2015 ), SSD ( Fei-Fei et al.,

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AWS Machine Learning Blog

APRIL 7, 2025

You can use state-of-the-art model architecturessuch as language models, computer vision models, and morewithout having to build them from scratch. These pre-trained models serve as powerful starting points that can be deeply customized to address specific use cases. billion to a projected $574.78 billion in 2017 to a projected $37.68

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Machine Learning Large Language Models Python Automation 62

Unite.AI

AUGUST 5, 2024

I received my masters in Civil/Environmental Engineering from Stanford University in 2016. PowerAI uses computer vision and machine learning to automate a huge portion of the fault detection process. During this time I took classes specializing in energy engineering, building my interest that started overseas.

Machine Learning 144

Machine Learning Artificial Intelligence Artificial Intelligence Computer Vision 144

Unite.AI

AUGUST 1, 2024

Secure Redact uses advanced machine learning and computer vision techniques to recognize and redact personally identifiable information (PII) in various image and video contexts, such as faces and license plates. How does Secure Redact leverage AI to automate the redaction of personal and sensitive data in video footage?

Machine Learning 144

Machine Learning Deep Learning Automation Computer Vision 144

Viso.ai

OCTOBER 7, 2024

billion tons of municipal solid waste was generated globally in 2016 with experts predicting a steep rise to 3.40 This is where computer vision technology can help identify waste, separate it, and ensure its proper disposal. In this article, we will propose computer vision as an effective tool for waste management.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

Both the images and tabular data discussed in this post were originally made available and published to GitHub by Ahmed and Moustafa (2016). Summary This post demonstrated how to use computer vision enabled by a foundation model to improve a classic ML use case using the SageMaker platform. References Ahmed, E.

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ML Machine Learning Computer Vision Auto-classification 102

Viso.ai

OCTOBER 15, 2024

About us : Viso Suite is an End-to-End Computer Vision Infrastructure that provides all the tools required to train, build, deploy, and manage computer vision applications at scale. To get started with enterprise-grade computer vision infrastructure, book a demo of Viso Suite with our team of experts.

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Viso.ai

FEBRUARY 28, 2023

And why is OpenCV so popular in the Computer Vision Industry? Hence, the world’s leading companies across industries use OpenCV to develop their computer vision systems. What is Computer Vision? Leading organizations use it to build, deploy and scale real-world computer vision applications.

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. Let’s get started!

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Artificial Corner

APRIL 19, 2024

Nearly 250 years later, in 2016, Amazon executed a similar stunt. However, the real breakthrough in this AI advancement, which integrated technologies such as Computer Vision, Sensor Fusion, and Deep Learning, relied significantly on about 1000 individuals in India.

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AI AI Computer Vision Deep Learning 98

Viso.ai

DECEMBER 4, 2023

For enterprise applications using TensorFlow, check out the computer vision platform Viso Suite which automates the end-to-end infrastructure around serving a TensorFlow model at scale. PyTorch Overview PyTorch was first introduced in 2016. One of the easiest ways to get started with TensorFlow Serving is with Docker.

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Neural Network Deep Learning Python Machine Learning 98

Google Research AI blog

OCTOBER 25, 2022

Posted by Rodrigo Benenson, Research Scientist, Google Research Open Images is a computer vision dataset covering ~9 million images with labels spanning thousands of object categories. Researchers around the world use Open Images to train and evaluate computer vision models.

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Explosion

NOVEMBER 9, 2016

2016) introduce an attention mechanism that takes two sentence matrices, and outputs a single vector: Yang et al. 2016) introduce an attention mechanism that takes a single matrix and outputs a single vector. 2016) presented a model that achieved 86.8% 2016) presented a model that achieved 86.8% For example, Bowman et al.

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). 2016)[ 91 ] You et al. Source : You et al. 2017) [ 96 ].

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Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Viso.ai

FEBRUARY 27, 2024

At this time, the only computer vision task supported by YOLOv9 is object detection. YOLOv2 Released in 2016, it could detect 9000+ object categories. The model architecture uses a Cross-stage Partial (CSP) Connection block as the backbone for a better gradient flow to reduce computational cost. 65.0% + AF [ 63 ] 43.6

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Neural Network Computer Vision Convolutional Neural Networks Python 52

Viso.ai

DECEMBER 17, 2024

After that, this framework has been officially opened to professional communities since 2016. It offers end-to-end functionalities for both artificial intelligence and computer vision tasks. Use Cases Frequently Asked Questions (FAQs) About us: Viso Suite is the end-to-end computer vision solution for enterprises.

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Deep Learning Computer Vision Neural Network Artificial Intelligence 52

Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. provides the only end-to-end computer vision application platform, Viso Suite. The software infrastructure is used by leading organizations to gather data, train YOLOv7 models, and deliver computer vision applications.

Algorithm 52

Algorithm Computer Vision Deep Learning Neural Network 52

Viso.ai

JULY 9, 2024

Object detection is one of the crucial tasks in Computer Vision (CV). Computer vision researchers introduced YOLO architecture (You Only Look Once) as an object-detection algorithm in 2015. About Us: At Viso.ai, we power Viso Suite, the most complete end-to-end computer vision platform.

Computer Vision 52

Computer Vision Neural Network Python Algorithm 52

Viso.ai

DECEMBER 18, 2023

YOLOv8 is the newest model in the YOLO algorithm series – the most well-known family of object detection and classification models in the Computer Vision (CV) field. offers the world’s leading end-to-end no-code Computer Vision Platform Viso Suite. Get a demo.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Algorithm 52

Heartbeat

MAY 11, 2023

The first version of YOLO was introduced in 2016 and changed how object detection was performed by treating object detection as a single regression problem. In the subfield of computer vision, the competition for cutting-edge object detection is fierce. Ability to detect objects in images quickly and dependably.

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Deep Learning Computer Vision Data Scientist ML 75

Mlearning.ai

JUNE 16, 2023

The ImageNet dataset, featuring natural images, contains 14,197,122 annotated images organized in 1000 classes and is commonly used as a benchmark for many computer vision models⁸. This “transfer learning” approach was so successful that it became the de-facto standard for solving a broad range of computer vision problems.

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Viso.ai

JULY 17, 2024

Fast Style Transfer (2016) While the previous model produced decent results, it was computationally expensive and slow. In 2016, Justin Johnson, Alexandre Alahi, and Li Fei-Fei addressed computation limitations by publishing their research paper titled “Perceptual Losses for Real-Time Style Transfer and Super-Resolution.”

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

MARCH 1, 2023

2016) This paper introduced DCGANs, a type of generative model that uses convolutional neural networks to generate images with high fidelity. The company is best known for NLP tools, but also enables the use of computer vision, audio, and multimodal models. Attention Is All You Need Vaswani et al.

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Mlearning.ai

MARCH 9, 2023

In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2012; Otsu, 1979; Long et al., 3431–3440).

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Deep Learning Computer Vision Machine Learning Algorithm 52

Heartbeat

JUNE 14, 2023

Rethinking the inception architecture for computer vision. Proceedings of the IEEE conference on computer vision and pattern recognition. Proceedings of the IEEE international conference on computer vision. Eighth JPL Airborne Geoscience Workshop. 4] Szegedy, Christian, et al. When does label smoothing help?

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Neural Network Computer Vision Deep Learning Explainability 59