Marktechpost

OCTOBER 30, 2023

Researchers have challenged the prevailing belief in the field of computer vision that Vision Transformers (ViTs) outperform Convolutional Neural Networks (ConvNets) when given access to large web-scale datasets. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

NOVEMBER 10, 2023

In image recognition, researchers and developers constantly seek innovative approaches to enhance the accuracy and efficiency of computer vision systems. All credit for this research goes to the researchers of this project. Check out the Paper. If you like our work, you will love our newsletter.

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Heartbeat

DECEMBER 20, 2023

This blog aims to equip you with a thorough understanding of these powerful neural network architectures. Whether you’re a seasoned AI researcher or a budding enthusiast in machine learning, the insights offered here will deepen your understanding and guide you in leveraging the full potential of CNNs in various applications.

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Marktechpost

JUNE 19, 2023

Instance segmentation refers to the computer vision task of identifying and differentiating multiple objects that belong to the same class within an image by treating them as distinct entities. For instance, convolutional neural networks (CNNs) and other progressive architectures such as Mask R-CNN are used for instance segmentation.

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Marktechpost

OCTOBER 21, 2023

To combine computer-generated visuals or deduce the physical characteristics of a scene from pictures, computer graphics, and 3D computer vision groups have been working to create physically realistic models for decades. All Credit For This Research Goes To the Researchers on This Project.

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AI Weekly

JUNE 29, 2023

Lyndsey Jones, publishing consultant, digital transformation expert, strategic advisor and coach, shares her views about how to navigate an AI world where there is likely to be a further explosion of content creation in an overcrowded market. June 15, 2023 /PRNewswire/ -- Quantum Computing Inc. ("QCi"

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Marktechpost

JUNE 30, 2023

The first step depends on using a detector based on a Convolutional Neural Network (CNN). They show that a real-time model for any arbitrary data segment is feasible using the computational efficiency of convolutional neural networks (CNNs). Check Out the Paper and Github Repo.

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Viso.ai

DECEMBER 22, 2023

The Segment Anything Model (SAM), a recent innovation by Meta’s FAIR (Fundamental AI Research) lab, represents a pivotal shift in computer vision. SAM performs segmentation, a computer vision task , to meticulously dissect visual data into meaningful segments, enabling precise analysis and innovations across industries.

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Marktechpost

OCTOBER 1, 2023

In recent years, vision transformers (ViTs) have become a potent architecture for various vision applications, including object identification and picture classification. All Credit For This Research Goes To the Researchers on This Project. If you like our work, you will love our newsletter.

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Marktechpost

JUNE 24, 2023

They also evaluate the method against a state-of-the-art convolutional neural network (CNN) model used for forensic picture classification and find that their methods perform better. According to the team, their method can be easily compromised by a cropping attack, which is a major disadvantage.

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Marktechpost

SEPTEMBER 12, 2023

Modern algorithms for fine-grained image classification frequently rely on convolutional neural networks (CNN) and vision transformers (ViT) as their structural basis. All Credit For This Research Goes To the Researchers on This Project. If you like our work, you will love our newsletter.

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Marktechpost

JULY 5, 2023

Forecasting and downscaling can be analogous to a variety of computer vision tasks. More sophisticated deep learning algorithms like residual convolutional neural networks, U-nets, and vision transformers are also available. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

JANUARY 13, 2024

There has been a dramatic increase in the complexity of the computer vision model landscape. Many models are now at your fingertips, from the first ConvNets to the latest Vision Transformers. To fill this gap, a new study by MBZUAI and Meta AI Research investigates model characteristics beyond ImageNet correctness.

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Marktechpost

JULY 23, 2023

Deep learning has significantly advanced face recognition models based on convolutional neural networks. All Credit For This Research Goes To Researchers on This Project. Also, don’t forget to join our Reddit page and discord channel , where we share the latest AI research news, cool AI projects, and more.

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Marktechpost

JUNE 22, 2023

Paella utilizes a pre-trained encoder-decoder architecture based on a convolutional neural network, with the capacity to represent a 256×256 image using 256 tokens selected from a set of 8,192 tokens learned during pretraining. The model was trained on 900 million image-text pairs from LAION-5B aesthetic dataset.

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Marktechpost

AUGUST 15, 2023

Detecting these videos requires combining techniques like analyzing facial movements, textures, and temporal consistency, often utilizing machine learning like convolutional neural networks (CNNs). All Credit For This Research Goes To the Researchers on This Project.

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Topbots

OCTOBER 4, 2023

Image processing : Predictive image processing models, such as convolutional neural networks (CNNs), can classify images into predefined labels (e.g., Masking in BERT architecture ( illustration by Misha Laskin ) Another common type of generative AI model are diffusion models for image and video generation and editing.

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The MLOps Blog

NOVEMBER 14, 2023

Example of a deep learning visualization: small convolutional neural network CNN, notice how the thickness of the colorful lines indicates the weight of the neural pathways | Source How is deep learning visualization different from traditional ML visualization?

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The MLOps Blog

FEBRUARY 22, 2024

You can implement architectural approaches, for example, by creating dedicated, specialized subnetworks like in Progressive Neural Networks or by simply having multiple model heads (last layers), which are selected based on the input data characteristics (which can be, for example, the task label in task-incremental scenarios).

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Viso.ai

DECEMBER 1, 2023

In particular, we will cover the following: Concepts of AI vs. ML vs. DL What is an AI model, what’s an ML model, or a DL model? Artificial Intelligence (AI) Artificial Intelligence (AI) is a subfield within computer science associated with constructing machines that can simulate human intelligence.

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Marktechpost

JUNE 27, 2023

Be aware that some AI models have been taught to purposefully make outputs without connection to real-world input (data). AI hallucinations can take many different shapes, from creating false news reports to false assertions or documents about persons, historical events, or scientific facts.

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Kavita Ganesan

JANUARY 27, 2022

It provides an introduction to deep neural networks in Python. Andrew is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations. Neural Network Basics We will start with some basics on neural networks.

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Marktechpost

JULY 18, 2023

Finding objects in images has been a long-going task in computer vision. The first stage employs a Convolutional Neural Network (CNN)-based detector to produce segmentation masks for all instances in the image. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

JULY 16, 2023

The Vision Transformer (ViT) rapidly replaces convolution-based neural networks because of its simplicity, flexibility, and scalability. Feeding data into a deep neural network during training and operation in batches is common practice. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

JULY 24, 2023

Object detection and image segmentation are crucial tasks in computer vision and artificial intelligence. Because of their capacity to learn hierarchical representations of picture input, Convolutional Neural Networks (CNNs) have become the go-to option for these problems.

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Marktechpost

JULY 18, 2023

The science of computer vision has recently seen dramatic changes in object identification, which is often regarded as a difficult area of study. Object localization and classification is a difficult area of study in computer vision because of the complexity of the two processes working together.

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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. Practitioners first trained a Convolutional Neural Network (CNN) to perform image classification on ImageNet (i.e. pre-training).

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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.

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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). Building on seminal work from Kiros et al.

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Viso.ai

DECEMBER 21, 2023

Over the past decade, the field of computer vision has experienced monumental artificial intelligence (AI) breakthroughs. This blog will introduce you to the computer vision visionaries behind these achievements. As we go down the list, we discuss the key contributions of every AI influencer.

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading! An experience that weighs learning heavily.

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John Snow Labs

MAY 8, 2024

Model Architecture The architecture of pathology-specific LLMs often incorporates multimodal learning frameworks, integrating NLP with computer vision (CV) to analyze both text and images.

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