AI Weekly

MARCH 21, 2024

By analysing the appeal of these tools, we provide a framework for advancing discussions of responsible knowledge production in the age of AI. Join the AI conversation and transform your advertising strategy with AI weekly sponsorship This RSS feed is published on [link].

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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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AI Weekly

DECEMBER 7, 2023

Connect with 5,000+ attendees including industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies. theconversation.com Who will win the battle for AI in the cloud? Our findings revealed that the DCNN, enhanced by this specialised training, could surpass.

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Marktechpost

JULY 14, 2023

This image representation comes under a broad category of Computer Vision and Convolutional Neural Networks. Researchers developed a Composed image retrieval (CIR) system to have a minimal loss, but the problem with this method was that it requires a large dataset for training the model.

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AI Weekly

OCTOBER 26, 2023

listverse.com Research A new method for safety helmet detection based on convolutional neural network Using the designed channel attention module and location attention module, adjacent shallow feature maps and upsampled feature maps are adaptively fused to generate new feature maps with strong semantics and precise location information.

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Marktechpost

JULY 21, 2023

Researchers at HAI find that due to the statistical property of images in deep neural networks, visual numerosity arises, and quantity-sensitive neurons emerge spontaneously in convolution neural networks, which were trained to categorize objects in standardized ImageNet datasets.

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AI Weekly

JULY 27, 2023

businessinsider.com Robots should be "good neighbours and good citizens" says Madeline Gannon Robots should be "good neighbours and good citizens" says Madeline Gannon People are asking the wrong questions about humanity's relationship with AI argues Madeline Gannon. zdnet.com Sponsor Microsoft Office for $39.99!

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AssemblyAI

JANUARY 23, 2025

Unlike many natural language processing (NLP) models, which were historically dominated by recurrent neural networks (RNNs) and, more recently, transformers, wav2letter is designed entirely using convolutional neural networks (CNNs). Despite this, it remains widely recognized by its original name, wav2letter.

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Marktechpost

SEPTEMBER 4, 2023

Recent advancements in deep neural networks have enabled new approaches to address anatomical segmentation. For instance, state-of-the-art performance in the anatomical segmentation of biomedical images has been attained by deep convolutional neural networks (CNNs).

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Marktechpost

OCTOBER 11, 2023

Studies now investigate if building AI research agents with similar capabilities is possible. To evaluate AI research agents with free-form decision-making capabilities, researchers from Stanford University propose MLAgentBench, the first benchmark of its kind. Join our AI Channel on Whatsapp.

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Marktechpost

JULY 21, 2023

Researchers experimented in two stages: interview conversation under three topics (self-introduction topic, supervisor topic, and campus life topic) and a questionnaire evaluation. In Study 1, researchers used the facial emotion detection method to analyze the emotional features from the recorded video frames.

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AWS Machine Learning Blog

MARCH 21, 2025

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Marktechpost

NOVEMBER 16, 2023

A new research paper presents a deep learning-based classifier for age-related macular degeneration (AMD) stages using retinal optical coherence tomography (OCT) scans. The two-stage convolutional neural network accurately classified macula-centered 3D volumes into four classes: Normal, iAMD, GA, and nAMD.

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Marktechpost

SEPTEMBER 12, 2023

It leverages the capabilities of deep learning models, such as Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs). 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

AUGUST 25, 2023

The researcher’s approach features the images onto a voxel grid and directly predicts the scene’s truncated signed distance function (TSDF) using a 3D convolution neural network. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

DECEMBER 29, 2023

To overcome these obstacles and raise the precision and adaptability of awn analysis, the research team suggests enlarging the training set and investigating different convolutional neural network (CNN) models. Researchers used binary cross-entropy loss and Dice Coefficient (DC) for training and validating the model.

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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). Segmentation masks for each instance in the image are generated.

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Marktechpost

OCTOBER 21, 2023

These models were the basis for the generative AI tools mentioned above and were trained on an enormous cloud of powerful graphics processing units (GPUs). All Credit For This Research Goes To the Researchers on This Project. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter.

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Marktechpost

NOVEMBER 30, 2023

The research outlines the development of a machine learning-based binary classifier capable of detecting an elusive icosahedral quasicrystal (i-QC) phase from multiphase powder X-ray diffraction patterns. The researchers constructed a binary classifier employing 80 convolutional neural networks.

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Marktechpost

NOVEMBER 15, 2023

An adaptive softmax Convolutional Neural Network (CNN) kernel is utilized in the lower blocks, with its kernel size determined by the timestep and speaker. All credit for this research goes to the researchers of this project. If you like our work, you will love our newsletter. We are also on Telegram and WhatsApp.

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Marktechpost

OCTOBER 1, 2023

This is because, whereas the size of the convolutional kernel constrains convolutional neural networks (CNNs) and can only extract local information, self-attention can remove global information from the picture, delivering adequate and meaningful visual characteristics. If you like our work, you will love our newsletter.

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Marktechpost

NOVEMBER 21, 2023

The team developed a neural network that allows them to represent a large system in a very compact way. All credit for this research goes to the researchers of this project. The post Revolutionizing Data Reconstruction: AI’s Compact Solution for Broad Information Retrieval appeared first on MarkTechPost.

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Marktechpost

OCTOBER 10, 2023

Its applications are used in many fields, such as image and speech recognition for language processing, object detection, and medical imaging diagnostics; finance for algorithmic trading and fraud detection; autonomous vehicles using convolutional neural networks for real-time decision-making; and recommendation systems for personalized content.

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Marktechpost

JUNE 15, 2023

Convolutional neural networks can use Images with translational symmetry, and permutation symmetry in graphs can be used by graph neural networks. Theoretical research and practical methods for constructing general group equivariant neural networks have seen a recent uptick in interest.

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Marktechpost

SEPTEMBER 29, 2024

In response, Google utilizes a deep neural network, CTG-net, to process the time-series data of fetal heart rate (FHR) and uterine contractions (UC) in order to predict fetal hypoxia. The CTG-net model utilizes a convolutional neural network (CNN) architecture to analyze FHR and UC signals, learning their temporal relationships.

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Marktechpost

DECEMBER 15, 2023

CNNs (Convolutional neural networks) have become a popular technique for image recognition in recent years. However, new challenges have emerged as these networks have grown more complex. All credit for this research goes to the researchers of this project. If you like our work, you will love our newsletter.

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Marktechpost

DECEMBER 15, 2023

Compared to trilinear interpolation and a classical convolutional neural network, the generative model reconstructs the resolution-dependent extreme value distribution with high skill. All credit for this research goes to the researchers of this project. It showed a high fractions skill score of 0.6

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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

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

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. If you like our work, you will love our newsletter. We are also on Telegram and WhatsApp.

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Marktechpost

DECEMBER 24, 2023

Deep Learning: This branch of machine learning involves convolutional neural networks (CNN), which have gained prominence due to their ability to extract features from images automatically, reducing the reliance on manual feature engineering. All credit for this research goes to the researchers of this project.

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Marktechpost

SEPTEMBER 1, 2023

They found that the careful selection of algorithms significantly influences authentication performance, with Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) emerging as leaders in handling physiological and behavioral dynamics. If you like our work, you will love our newsletter.

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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 18, 2023

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. This AI Approach Speeds Up the SAM Model appeared first on MarkTechPost.

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Marktechpost

JULY 16, 2023

Due to this and the inherent architectural constraints of convolutional neural networks, it has become common practice to either resize or pad images to a predetermined size. All Credit For This Research Goes To the Researchers on This Project.

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Marktechpost

DECEMBER 12, 2023

The FGS has been used to predict facial landmark placements and pain scores by utilizing deep neural networks and machine learning models. All credit for this research goes to the researchers of this project. If you like our work, you will love our newsletter.

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Unite.AI

OCTOBER 22, 2024

Initially, many AI algorithms operated within manageable complexity limits. Training neural networks, especially deep architectures like Convolutional Neural Networks (CNNs) and transformers, requires processing vast amounts of data and parameters, leading to high computational costs.

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