AI Weekly

JULY 27, 2023

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation. Get it today!]

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Analytics Vidhya

MARCH 30, 2022

Introduction AI and machine vision, which were formerly considered futuristic technology, has now become mainstream, with a wide range of applications ranging from automated robot assembly to automatic vehicle guiding, analysis of remotely sensed images, and automated visual inspection. Computer vision and deep learning […].

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Marktechpost

NOVEMBER 16, 2024

Learning computer vision is essential as it equips you with the skills to develop innovative solutions in areas like automation, robotics, and AI-driven analytics, driving the future of technology. Computer Vision The Computer Vision Nanodegree Program offers advanced training in computer vision, deep learning, and robotics.

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AI Weekly

JUNE 29, 2023

AI is rightly touted as a massively powerful tool biztoc.com Robotics Meet the robots attending the UN’s ‘AI for Good Global’ summit At a UN summit in Geneva next week, tech luminaries ranging from futurist Ray Kurzweil to DeepMind COO Lila Ibrahim will discuss AI for good. phys.org Quantum Computing Inc.

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Marktechpost

JUNE 3, 2024

Its AI courses offer hands-on training for real-world applications, enabling learners to effectively use Intel’s portfolio in deep learning, computer vision, and more. It covers AI fundamentals, including supervised learning and deep learning basics, without complex math.

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Marktechpost

MARCH 22, 2024

The advent of deep learning propelled the field forward, offering improved accuracy but at the expense of computational efficiency. This dichotomy is particularly pronounced in scenarios requiring instantaneous visual data processing, such as autonomous vehicles, robotic navigation, and interactive augmented reality systems.

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Heartbeat

MARCH 14, 2023

As robots need to be able to pick up on their surroundings and adapt accordingly, this is a crucial skill for the field. In this article, I would like to take a look at the current challenges in the field of robotics and discuss the relevance and applications of computer vision in this area.

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Viso.ai

DECEMBER 3, 2023

How pose estimation works: Deep learning methods Use Cases and pose estimation applications How to get started with AI motion analysis Real-time full body pose estimation in construction – built with Viso Suite About us: Viso.ai Today, the most powerful image processing models are based on convolutional neural networks (CNNs).

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Marktechpost

NOVEMBER 20, 2024

Some researchers have introduced multi-architectural modular deep neural networks to reduce false positives in anomaly detection. Others have proposed a hybrid network intrusion detection system integrating convolutional neural networks (CNN), fuzzy C-means clustering, genetic algorithm, and a bagging classifier.

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Marktechpost

DECEMBER 24, 2023

By addressing the limitations observed in prior surveys, this comprehensive study aims to bridge the gap by encompassing a broader spectrum of ML techniques, from traditional to deep learning and augmented learning. Deep learning methods have shown robust performance in classifying leaf diseases.

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Viso.ai

DECEMBER 3, 2023

The recent deep learning algorithms provide robust person detection results. However, deep learning models such as YOLO that are trained for person detection on a frontal view data set still provide good results when applied for overhead view person counting ( TPR of 95%, FPR up to 0.2% ).

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Marktechpost

DECEMBER 10, 2024

1943: McCulloch and Pitts created a mathematical model for neural networks, marking the theoretical inception of ANNs. 1958: Frank Rosenblatt introduced the Perceptron , the first machine capable of learning, laying the groundwork for neural network applications. How Do Artificial Neural Networks Work?

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Marktechpost

SEPTEMBER 9, 2024

Learning computer vision is essential as it equips you with the skills to develop innovative solutions in areas like automation, robotics, and AI-driven analytics, driving the future of technology. Computer Vision The Computer Vision Nanodegree Program offers advanced training in computer vision, deep learning, and robotics.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

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Viso.ai

FEBRUARY 25, 2023

The scene is parted into different classes such as “building”, “road”, “tree” In the last 40 years, various segmentation methods have been proposed, ranging from MATLAB image segmentation and traditional computer vision methods to the state of the art deep learning methods.

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Marktechpost

DECEMBER 1, 2023

Applications include better human-computer interaction and improved emotional response in robots, making FER crucial in human-machine interface technology. Early approaches heavily relied on manually crafted features and machine learning algorithms such as support vector machines and random forests.

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Pickl AI

SEPTEMBER 25, 2024

Summary: This blog delves into 20 Deep Learning applications that are revolutionising various industries in 2024. From healthcare to finance, retail to autonomous vehicles, Deep Learning is driving efficiency, personalization, and innovation across sectors.

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Pickl AI

FEBRUARY 1, 2023

Transfer Learning in Deep Learning: A Brief Overview Collecting large volumes of data, filtering it and then interpreting is a challenging task. Yes, Transfer Learning is the answer to it. What is Transfer Learning? Eventually, making it a powerful and efficient tool in Machine Learning.

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Viso.ai

JUNE 10, 2024

This system has applications in various fields such as filmmaking, video production, animation, sports analysis, robotics, and augmented reality. Marker-less Systems: Currently, modern systems use computer vision and deep learning to track motion without markers. The concept of motion tracking has been in existence for decades.

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Heartbeat

APRIL 23, 2023

Photo by RetroSupply on Unsplash Introduction Deep learning has been widely used in various fields, such as computer vision, NLP, and robotics. The success of deep learning is largely due to its ability to learn complex representations from data using deep neural networks.

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Viso.ai

MAY 1, 2024

Deep learning and Convolutional Neural Networks (CNNs) have enabled speech understanding and computer vision on our phones, cars, and homes. Home Robots: over the next 15 years, mechanical and AI technologies will increase home robots’ reliable usage in a typical household. Brooks et al.

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Viso.ai

MARCH 26, 2024

The introduction of the Transformer model was a significant leap forward for the concept of attention in deep learning. Uniquely, this model did not rely on conventional neural network architectures like convolutional or recurrent layers. without conventional neural networks. Vaswani et al.

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Marktechpost

JULY 24, 2023

Many studies have been motivated to explore hidden hierarchical patterns in the large volume of weather datasets for weather forecasting due to the recent development of deep learning techniques, the widespread availability of massive weather observation data, and the advent of information and computer technology.

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Heartbeat

MAY 30, 2023

It combines reinforcement learning (RL), a type of learning in which an agent learns through examinations and experimentations by receiving rewards or punishments based on its actions, with deep learning. This machine learning subset uses artificially generated neural networks to model complex data relationships.

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Viso.ai

OCTOBER 7, 2024

This is where we find opportunities for combining robotics with computer vision. Waste-sorting robots equipped with cameras and sensors detect these materials in real time. Trained on extensive datasets, these robots accurately sort waste and direct it to the appropriate path for recycling or disposal. plastic, metal, paper).

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AWS Machine Learning Blog

MARCH 30, 2023

The model extracts features from the image using a convolutional neural network. He has been working on human-in-the-loop optimization since 1995, when he applied the LeNet Convolutional Neural Network to check recognition. As input, the model takes an image and a corresponding bounding box annotation.

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NVIDIA

DECEMBER 21, 2023

DigitalPath, based in Chico, California, has refined a convolutional neural network to spot wildfires. The NVIDIA Jetson Orin -based robots-as-a-service business provides farmers with metrics on yield gains and chemical reduction. “We Burning for solutions, developers are embracing AI for early detection.

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Viso.ai

FEBRUARY 23, 2024

Our software enables ML teams to train deep learning and machine learning models and deploy them in computer vision applications – completely end-to-end. For more details, check out our Image Segmentation Using Deep Learning article. Modern machine learning has come a long way. Get a demo.

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Viso.ai

OCTOBER 10, 2024

Popular applications include speech recognition, text pattern recognition, facial recognition, movement recognition, recognition for video deep learning analysis, and medical image recognition in healthcare. In recent years, deep learning has proven to be the most successful method to solve recognition tasks.

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PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

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Google Research AI blog

FEBRUARY 23, 2023

We see this same accelerated pattern in translating our research on deep learning for low-dose CT scans to lung cancer screening workflows through our partnership with RadNet’s Aidence. Genomics is another area where partnership has proven a powerful accelerant for ML technology.

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Pickl AI

AUGUST 5, 2024

DRL has been successfully applied to various domains, including gaming, robotics, and finance, demonstrating its potential to solve challenging real-world problems. Introduction Deep Reinforcement Learning (DRL) is a rapidly advancing field that combines the power of Deep Learning with the principles of reinforcement learning.

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Heartbeat

JANUARY 15, 2024

We will also compare their performance with the formidable deep learning-based segmentation techniques, bringing out the unique strengths of each approach. Real-time segmentation using snakes has proven invaluable in robotics, enabling robots to navigate and interact with their environment autonomously.

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Viso.ai

APRIL 11, 2024

Researchers apply a deep learning model to identify potential objects within an image. The detection step utilizes region proposal networks to identify and mark regions that probably contain objects. Detection applies a deep learning model to identify potential objects within an image. What’s Next?

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Pickl AI

AUGUST 14, 2024

Neural networks come in various forms, each designed for specific tasks: Feedforward Neural Networks (FNNs) : The simplest type, where connections between nodes do not form cycles. The resurgence of neural networks in the 1980s was marked by the development of backpropagation, a method for training multi-layer networks.

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Heartbeat

DECEMBER 8, 2023

He focused on generative AI trained on large language models, The strength of the deep learning era of artificial intelligence has lead to something of a renaissance in corporate R&D in information technology, according to Yann LeCun, chief AI. Hinton is viewed as a leading figure in the deep learning community.

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