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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Marktechpost

DECEMBER 29, 2023

Consequently, the researchers of Plant Phenomics have introduced BarbNet, a deep-learning model designed specifically for the automated detection and phenotyping of barbs in microscopic images of awns. Researchers used binary cross-entropy loss and Dice Coefficient (DC) for training and validating the model.

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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 research details creating a deep learning-based system for automated AMD detection and staging using retinal OCT scans.

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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. It signifies a leap towards more creative, efficient, and flexible AI applications, reshaping customer experiences and operational.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Marktechpost

NOVEMBER 30, 2023

Addressing this challenge, a study by researchers from Tokyo University of Science (TUS), Japan, in collaboration with esteemed institutions, introduced a new deep learning model. The researchers constructed a binary classifier employing 80 convolutional neural networks.

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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.

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Marktechpost

OCTOBER 10, 2023

Deep learning, a machine learning subset, automatically learns complex representations from the input. Convolutional neural networks (CNNs) and vision transformers (ViT), two examples of deep learning models for computer vision, analyze signals by assuming planar (flat) regions.

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Marktechpost

SEPTEMBER 1, 2023

Researchers have been exploring behavioral and physiological biometrics for enhancing mobile device security. Incorporating machine learning and deep learning algorithms has shown promise in bolstering security. It builds upon previous research in this field and identifies trends in authentication dynamics.

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Marktechpost

DECEMBER 15, 2023

In this manner, from coarsely resolved data, the GAN learns how to produce realistic precipitation fields and determine their temporal sequence. Compared to trilinear interpolation and a classical convolutional neural network, the generative model reconstructs the resolution-dependent extreme value distribution with high skill.

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Heartbeat

DECEMBER 20, 2023

We delve into the intricacies of Residual Networks (ResNet), a groundbreaking architecture in CNNs. Understanding why ResNet is essential, its innovative aspects, and what it enables in deep learning forms a crucial part of our exploration. Why We Need ResNet Let’s imagine that we had a shallow network that was performing well.

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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

SEPTEMBER 29, 2024

Google researchers addressed the challenge of variability and subjectivity in clinical experts’ interpretation of visual cardiotocography (CTG), specifically focusing on predicting fetal hypoxia, a dangerous condition of oxygen deprivation during labor, using deep learning techniques. Check out the Paper and Details.

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AWS Machine Learning Blog

MARCH 21, 2025

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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. The post These Fully Automated Deep Learning Models Can Be Used For Pain Prediction Using The Feline Grimace Scale (FGS) With Smartphone Integration appeared first on MarkTechPost.

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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

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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Unite.AI

OCTOBER 22, 2024

Understanding Computational Complexity in AI The performance of AI models depends heavily on computational complexity. In AI, particularly in deep learning , this often means dealing with a rapidly increasing number of computations as models grow in size and handle larger datasets.

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Unite.AI

JUNE 21, 2024

The Rise of CUDA-Accelerated AI Frameworks GPU-accelerated deep learning has been fueled by the development of popular AI frameworks that leverage CUDA for efficient computation. NVIDIA's commitment to open-source initiatives has been a driving force behind the widespread adoption of CUDA in the AI research community.

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Marktechpost

JUNE 15, 2023

In deep learning, symmetry is a crucial inductive bias. Convolutional neural networks can use Images with translational symmetry, and permutation symmetry in graphs can be used by graph neural networks. This may include non-connected Lie group symmetry, nonlinear symmetry, and gauge symmetry.

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Marktechpost

JULY 18, 2023

Traditional approaches use handcrafted features, and more recent advancements have brought us models driven by deep learning models. The first stage employs a Convolutional Neural Network (CNN)-based detector to produce segmentation masks for all instances in the image. The post Segment Anything, but Faster!

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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. Deep learning models frequently unintentionally concentrate more on backgrounds, occasionally to the point where they can categorize based only on it.

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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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Marktechpost

JULY 5, 2023

Deep learning research has exploded in recent years, and scientists studying machine learning and climate change are now looking into how deep learning techniques might address weather forecasting and spatial downscaling issues. All Credit For This Research Goes To the Researchers on This Project.

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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

JUNE 22, 2023

These models have completely transformed how textual descriptions can be used to generate high-quality images by harnessing the power of deep learning algorithms. In order to add noise to their example during the training phase, the researchers included some randomly chosen tokens in this list as well.

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Marktechpost

SEPTEMBER 17, 2023

In protein sequence evolution, EvoDiff is the first deep-learning framework to showcase the efficacy of diffusion generative modeling. Using the dilated convolutional neural network architecture first seen in the CARP protein masked language model, they trained all EvoDiff sequence models on 42M sequences from UniRef50.

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Marktechpost

JUNE 19, 2023

Over the past few years, there has been a significant upturn in the number of instances of segmentation techniques because of the rapid advancements in deep learning techniques. 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

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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Viso.ai

FEBRUARY 11, 2024

One of the crucial tasks in today’s AI is the image classification. Image classification employs AI-based deep learning models to analyze images and perform object recognition, as well as a human operator. It is one of the largest resources available for training deep learning models in object recognition tasks.

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Marktechpost

JUNE 27, 2023

Deep Convolutional Neural Networks (DCNN) trained on millions of photos power VanceAI’s A.I. VanceAI uses deep learning to its full potential because its method is distinct from tools based on traditional mathematical procedures. tools, allowing for insightful analysis and lightning-fast processing.

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How to Learn Machine Learning

DECEMBER 15, 2024

Deep Learning Specialization Developed by deeplearning.ai Sale Why Machines Learn: The Elegant Math Behind Modern AI Hardcover Book Ananthaswamy, Anil (Author) English (Publication Language) 480 Pages - 07/16/2024 (Publication Date) - Dutton (Publisher) Buy on Amazon 3.

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Viso.ai

DECEMBER 1, 2023

AI vs. Machine Learning vs. Deep Learning First, it is important to gain a clear understanding of the basic concepts of artificial intelligence types. We often find the terms Artificial Intelligence and Machine Learning or Deep Learning being used interchangeably. Get the Whitepaper or a Demo.

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Marktechpost

AUGUST 15, 2023

Various algorithms leveraging deep learning and facial landmarks have demonstrated captivating outcomes in tackling this challenge. Detecting these videos requires combining techniques like analyzing facial movements, textures, and temporal consistency, often utilizing machine learning like convolutional neural networks (CNNs).

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Viso.ai

JANUARY 24, 2025

Architecture of LeNet5 – Convolutional Neural Network – Source The capacity of AGI to generalize and adapt across a broad range of tasks and domains is one of its primary features. Complex Training Process Deep Learning Large-scale datasets must be available for AGI system training.

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ODSC - Open Data Science

SEPTEMBER 17, 2024

Caffe Caffe is a deep learning framework focused on speed, modularity, and expression. It’s particularly popular for image classification and convolutional neural networks CNNs. TensorFlow’s extensive community and robust documentation make it a go-to framework for software engineers exploring deep learning.

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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., The predictive AI algorithms can be used to predict a wide range of variables, including continuous variables (e.g., Sign up for more AI research updates.

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