Unite.AI

NOVEMBER 6, 2023

With these advancements, it’s natural to wonder: Are we approaching the end of traditional machine learning (ML)? In this article, we’ll look at the state of the traditional machine learning landscape concerning modern generative AI innovations. What is Traditional Machine Learning? What are its Limitations?

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Analytics Vidhya

OCTOBER 9, 2022

Introduction In recent times, whenever we wish to perform image segmentation in machine learning, the first model we think of is the U-Net. U-Net is an encoder-decoder convolutional neural network with […]. It has been revolutionary in performance improvement compared to previous state-of-the-art methods.

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Marktechpost

JANUARY 9, 2024

Deep learning methods have been widely employed for early disease detection to tackle this challenge, showcasing remarkable classification accuracy and data synthesis to bolster model training. The study acknowledges the limited research effort in investigating multimodal images related to breast cancer using deep learning techniques.

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Marktechpost

JUNE 9, 2024

Deep learning methods excel in detecting cardiovascular diseases from ECGs, matching or surpassing the diagnostic performance of healthcare professionals. Researchers at the Institute of Biomedical Engineering, TU Dresden, developed a deep learning architecture, xECGArch, for interpretable ECG analysis.

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Pickl AI

JANUARY 29, 2025

Summary: This article presents 10 engaging Deep Learning projects for beginners, covering areas like image classification, emotion recognition, and audio processing. Each project is designed to provide practical experience and enhance understanding of key concepts in Deep Learning. What is Deep Learning?

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Unite.AI

DECEMBER 26, 2024

These deep learning algorithms get data from the gyroscope and accelerometer inside a wearable device ideally worn around the neck or at the hip to monitor speed and angular changes across three dimensions. Where does this data come from? One stream of data can be collected through a system of discreet cameras, radars, and sensors.

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Marktechpost

MARCH 10, 2025

This principle applies across various model classes, showing that deep learning isn’t fundamentally different from other approaches. However, deep learning remains distinctive in specific aspects. Another definition for benign overfitting is described as “one of the key mysteries uncovered by deep learning.”

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Pickl AI

JANUARY 26, 2025

Summary: Deep Learning models revolutionise data processing, solving complex image recognition, NLP, and analytics tasks. Introduction Deep Learning models transform how we approach complex problems, offering powerful tools to analyse and interpret vast amounts of data. With a projected market growth from USD 6.4

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AI News

JULY 27, 2023

The collaboration combines the strengths of three industry leaders: Graphcore, renowned for its Intelligence Processing Units (IPUs) hardware; UbiOps, a powerful machine learning operations (MLOps) platform; and Gcore Cloud, known for its robust cloud infrastructure. The event is co-located with Digital Transformation Week.

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Marktechpost

SEPTEMBER 10, 2023

Researchers think that high-speed testing using Deep Learning models can help us understand these effects better and speed up catalyst development. The way a catalyst’s surface is shaped matters for certain chemical reactions due to various properties of the catalyst, which we study in Surface Chemistry.

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Analytics Vidhya

FEBRUARY 16, 2022

Since 2012 after convolutional neural networks(CNN) were introduced, we moved away from handcrafted features to an end-to-end approach using deep neural networks. The post Classification without Training Data: Zero-shot Learning Approach appeared first on Analytics Vidhya.

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Marktechpost

MAY 5, 2024

In recent years, the demand for AI and Machine Learning has surged, making ML expertise increasingly vital for job seekers. Machine Learning with Python This course covers the fundamentals of machine learning algorithms and when to use each of them. and evaluating the same.

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Flipboard

NOVEMBER 16, 2024

Raw images are processed and utilized as input data for a 2-D convolutional neural network (CNN) deep learning classifier, demonstrating an impressive 95% overall accuracy against new images. The glucose predictions done by CNN are compared with ISO 15197:2013/2015 gold standard norms.

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Marktechpost

APRIL 12, 2024

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models.

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Marktechpost

MAY 7, 2024

Current computerized systems employ machine learning techniques, from shallow learning that relies on hand-crafted features to more advanced deep learning models that extract features directly from raw EEG data. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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Marktechpost

SEPTEMBER 1, 2023

Incorporating machine learning and deep learning algorithms has shown promise in bolstering security. In addition, the study highlights that hybrid schemes combining deep learning features with deep learning/machine learning classification can significantly improve authentication performance.

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AI Weekly

AUGUST 17, 2023

cmswire.com Why humans can't use NLP to speak with the animals We’ve already got machine-learning systems and natural language processors that can translate human speech into any number of existing languages, and adapting that process to convert animal calls into human-interpretable signals doesn’t seem that big of a stretch.

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NYU Center for Data Science

SEPTEMBER 25, 2024

CDS announced a new course in the center’s newly launched Lifelong Learning Program. Foundations of Deep Learning” offers CDS alumni the chance to dive into the latest advancements in AI and machine learning. It’s a chance for alumni to reconnect with groundbreaking research and applications in deep learning.

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Marktechpost

JANUARY 13, 2024

1/n) pic.twitter.com/LSXmEQiD2K — Zhuang Liu (@liuzhuang1234) January 8, 2024 The post How to Choose the Right Vision Model for Your Specific Needs: Beyond ImageNet Accuracy – A Comparative Analysis of Convolutional Neural Networks and Vision Transformer Architectures appeared first on MarkTechPost.

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Marktechpost

JANUARY 15, 2025

Traditional machine learning models, while effective in many scenarios, often struggle to process high-dimensional and unstructured data without extensive preprocessing and feature engineering. This gap has led to the evolution of deep learning models, designed to learn directly from raw data.

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Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. After you create a free account, you’ll have access to the best machine learning datasets. Importance and Role of Datasets in Machine Learning Data is king.

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AI Weekly

MARCH 21, 2024

nature.com Authorship attribution in twitter: a comparative study of machine learning and deep learning approaches This study proposes an AA approach using machine and deep learning algorithms to accurately predict the author of unknown posts on social media platforms.

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Flipboard

JANUARY 9, 2025

This finding highlights a simple mechanism for feature learning that can take place in overparametrized shallow convolutional neural networks, but not in shallow fully-connected architectures or in locally connected neural networks without weight sharing.

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Marktechpost

AUGUST 2, 2024

Deep learning has become a powerful tool for classifying pathological voices, particularly in the GRBAS (Grade, Roughness, Breathiness, Asthenia, Strain) scale assessment. The machine learning model was a 5-layer 1D-CNN, constructed and evaluated using TensorFlow. The training process was conducted without noise data.

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AI Weekly

DECEMBER 7, 2023

techxplore.com Millions of new materials discovered with deep learning AI tool GNoME finds 2.2 deepmind.google Seeing 3D images through the eyes of AI This issue is resolved by Professor Zhang's paper, "RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds." Petrobras) has invested in six robots from ANYbotics.

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Marktechpost

APRIL 24, 2024

While traditional PAM analysis is time-consuming, recent advancements in deep learning technology offer promising solutions for automating bird species identification from audio recordings. Preliminary research in interpretable deep learning for audio includes deep prototype learning, initially proposed for image classification.

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Marktechpost

DECEMBER 24, 2023

In this critical realm, the transformative power of machine learning is reshaping the landscape. As the demand for sustainable agriculture grows, machine learning emerges as a vital force, reshaping the future of food security and cultivation.

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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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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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Pickl AI

SEPTEMBER 5, 2024

Summary: Convolutional Neural Networks (CNNs) are essential deep learning algorithms for analysing visual data. They automatically extract and learn features, making them ideal for tasks like image classification and object detection. What are Convolutional Neural Networks?

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Marktechpost

OCTOBER 8, 2024

They were recognized for their groundbreaking work in developing foundational machine learning technologies using artificial neural networks—work that has had a transformative impact on both the fields of physics and artificial intelligence. Hopfield of Princeton University and Geoffrey E.

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Towards AI

APRIL 7, 2024

With the emergence of ARCGISpro which will replace ArcMap by 2026 mainly focusing on data science and machine learning, all the signs that machine learning is the future of GIS and you might have to learn some principles of data science, but where do you start, let us have a look.

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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. Despite their importance is evident, analyzing these small structures has been challenging due to the lack of automated tools.

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Flipboard

FEBRUARY 26, 2025

In this study, we developed Miniset-DenseSENet, a convolutional neural network combining DenseNet121 with a Squeeze-and-Excitation attention mechanism, using 190 autopsy brain images from the Gregory Laboratory at the University of Aberdeen.

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Towards AI

SEPTEMBER 1, 2023

That’s where Machine Learning, and specifically Deep Learning, shines, abbreviating the processing time to mere minutes! ℝⁿ), which introduces greater complexity and requires the utilization of Deep Learning techniques. Applied in the more diverse domains such as aero spatial, automobile, energy, etc.,

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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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Unite.AI

OCTOBER 17, 2024

Healthcare in the United States is in the early stages of a significant potential disruption due to the use of Machine Learning and Artificial Intelligence. Some of the earliest and most extensive work has occurred in the use of deep learning and computer vision models. Several types of networks exist.

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