Marktechpost

NOVEMBER 23, 2023

It revealed key ambiguities in product categories, emphasizing the limitations of prediction accuracy and suggesting the need for label improvements. The post Decoding Complex AI Models: Purdue Researchers Transform Deep Learning Predictions into Topological Maps appeared first on MarkTechPost.

Deep Learning 122

Deep Learning AI Modeling Neural Network AI 122

Analytics Vidhya

DECEMBER 20, 2023

Introduction Data augmentation encompasses various techniques to expand and enhance datasets for machine learning and deep learning models. These methods span different categories, each altering data to introduce diversity and improve model robustness.

Deep Learning 259

Deep Learning Machine Learning Computer Vision Algorithm 259

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. in a real-world test set.

Deep Learning 101

Deep Learning Convolutional Neural Networks Neural Network Categorization 101

Towards AI

AUGUST 21, 2023

Machine Learning vs. AI vs. Deep Learning vs. Neural Networks: What’s the Difference? Amidst this backdrop, we often hear buzzwords like artificial intelligence (AI), machine learning (ML), deep learning, and neural networks thrown around almost interchangeably.

Neural Network 90

Neural Network Deep Learning Artificial Intelligence Artificial Intelligence 90

Marktechpost

DECEMBER 26, 2023

It emphasizes practical use cases over theoretical constructs, focusing on scenarios like identifying products from various categories. This approach contrasts with other metric learning libraries that are more tool-oriented. OML distinguishes itself by presenting an end-to-end solution tailored for real-world applications.

Deep Learning 116

Deep Learning Python Machine Learning Artificial Intelligence 116

Marktechpost

AUGUST 19, 2023

This falls under a broad category of Computer Vision. They also used various Machine Learning models in designing this system. To predict the structural colors of these arrays the researchers developed two Deep Learning models CSC and CSS.

Deep Learning 96

Deep Learning Computer Vision Machine Learning AI 96

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.

Deep Learning 52

Deep Learning Convolutional Neural Networks Computer Vision Neural Network 52

NVIDIA

OCTOBER 6, 2023

Researchers from the Universities of California at Berkeley and Santa Cruz, and the Technical University of Munich recently released a paper describing a new model that delivers deep learning to earthquake forecasting.

Deep Learning 89

Deep Learning Natural Language Processing Neural Network Machine Learning 89

Google Research AI blog

MARCH 14, 2023

To our knowledge, this is the first demonstration that medical experts can learn new prognostic features from machine learning, a promising start for the future of this “learning from deep learning” paradigm. In traditional ML, models learn from hand-engineered features informed by existing domain knowledge.

Deep Learning 95

Deep Learning ML Machine Learning Explainability 95

Marktechpost

DECEMBER 10, 2023

The research team from Carnegie Mellon University and Princeton University suggest a novel category of selected state space models, which enhances earlier research in several dimensions to get the Transformer-like modeling capability while maintaining a linear relationship with sequence length.

Deep Learning 121

Deep Learning Neural Network Machine Learning AI Researcher 121

Marktechpost

DECEMBER 16, 2023

Key Takeaways from the Paper: Diagnostic Potential: AI showcases promise in reclassifying cHCC-CCA into distinct categories of HCC or ICCA, offering a potential diagnostic breakthrough. These findings underscore the potential of AI in guiding more accurate diagnoses and prognostic markers for cHCC-CCA.

Deep Learning 79

Deep Learning Artificial Intelligence Artificial Intelligence AI Modeling 79

John Snow Labs

JUNE 2, 2023

Spark NLP’s deep learning models have achieved state-of-the-art results on sentiment analysis tasks, thanks to their ability to automatically learn features and representations from raw text data. During training, the model learns to identify patterns and features that are indicative of a certain sentiment.

Deep Learning 98

Deep Learning NLP Convolutional Neural Networks Neural Network 98

Marktechpost

JULY 27, 2023

Supervised deep learning models like Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA) have shown promise in identifying alcoholic beverages from images but require a vast amount of manually annotated data for training. The ABIDLA2 model outperformed ZSL in identifying specific beverage categories.

Deep Learning 52

Deep Learning Algorithm AI Researcher AI Research 52

Sebastian Ruder

FEBRUARY 23, 2023

This post gives a brief overview of modularity in deep learning. Fuelled by scaling laws, state-of-the-art models in machine learning have been growing larger and larger. We give an in-depth overview of modularity in our survey on Modular Deep Learning. Case studies of modular deep learning.

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. Another subfield that is quite popular amongst AI developers is deep learning, an AI technique that works by imitating the structure of neurons.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

IBM Journey to AI blog

MARCH 27, 2024

Within USEEIO, goods and services are categorized into 66 spend categories, referred to as commodity classes, based on their common environmental characteristics. This involves mapping the 15.909 sectors found across the Eora26 categories and more detailed national sector classifications to the USEEIO 66 spend categories.

ESG 194

ESG Categorization Large Language Models NLP 194

Unite.AI

JULY 21, 2023

The main aim of using Image Recognition is to classify images on the basis of pre-defined labels & categories after analyzing & interpreting the visual content to learn meaningful information. The model then detects and localizes the objects within the data, and classifies them as per predefined labels or categories.

Computer Vision 244

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 244

Marktechpost

JANUARY 24, 2024

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. However, deep neural networks are inaccurate and can produce unreliable outcomes. Then, they used a machine learning algorithm to determine data distribution mismatches based on forward-backward cycles.

Neural Network 103

Neural Network Deep Learning Data Mining Natural Language Processing 103

Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You may well come away thinking, deep learning is for ‘superhumans only’ — superhumans with supercomputers. Sounds interesting?

Deep Learning 52

Deep Learning Neural Network Machine Learning Computer Vision 52

Unite.AI

MARCH 28, 2024

It leverages deep learning algorithms to enable users to converse with chatbots. This deep level operational strategy allows today’s manufacturers to focus on their core competencies while leveraging the benefits of automation. ChatGPT is the latest technology driven by AI that uses natural language processing.

Robotics 333

Robotics Natural Language Processing Artificial Intelligence Artificial Intelligence 333

Heartbeat

MARCH 13, 2024

Using Comet to monitor pre-trained models Photo by Daniel Korpai on Unsplash Transfer learning involves using a pre-trained model to solve a deep-learning problem. Comet extensively integrates with multiple libraries, including the most common ones for deep learning, such as TensorFlow, Keras, and Pytorch.

Deep Learning 52

Deep Learning Data Scientist ML Explainability 52

Marktechpost

APRIL 21, 2024

Jina An open-source neural search framework that provides cloud-native neural search solutions powered by AI and deep learning. Pros: AI-driven, supports deep learning models, and is highly extensible. Cons: It can be overkill for simpler search tasks and requires deep learning expertise.

Deep Learning 105

Deep Learning Machine Learning Big Data Python 105

Marktechpost

JULY 22, 2023

TXGNN, a geometric deep learning technique for therapeutic usage prediction, is introduced by researchers interested in illnesses for which there needs to be more knowledgeable about their molecular causes and potential treatments. Finding novel medications is therapeutically significant, even for illnesses with therapies.

Deep Learning 52

Deep Learning Neural Network Machine Learning Explainability 52

Marktechpost

APRIL 5, 2024

While traditional neural networks can be embedded in pretopos categories, transformers necessarily reside in a topos completion. The proposed categorical framework not only enhances our understanding of transformers but also offers a novel perspective for future architectural advancements in deep learning.

Neural Network 124

Neural Network Natural Language Processing Categorization Explainability 124

Viso.ai

DECEMBER 19, 2023

Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! It uses AI-based deep learning models to analyze images with results that for specific tasks already surpass human-level accuracy (for example, in face recognition ).

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Viso.ai

MAY 6, 2024

And when it comes to technologies based on deep learning , that means vast and varied data sets to train on. This dataset consists of 13320 videos with 101 action categories, grouped into 25 groups and divided into 5 types. It’s a pre-trained network that can classify images into 1000 object categories.

Computer Vision 52

Computer Vision Deep Learning Neural Network Convolutional Neural Networks 52

Probably Approximately a Scientific Blog

AUGUST 14, 2018

Since I’ve started this blog 3 years ago, I’ve been refraining from writing about deep learning (DL), with the exception of occasionally discussing a method that uses it, without going into details. It’s a challenge to explain deep learning using simple concepts and without the caveat of remaining at a very high level.

Deep Learning 52

Deep Learning NLP Neural Network Machine Learning 52

Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. Image Recognition is the task of identifying objects of interest within an image and recognizing which category the image belongs to. Get a personalized demo. link] What is Image Recognition?

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Marktechpost

AUGUST 1, 2023

Deep learning and AI have made remarkable progress in recent years, especially in detection models. However, the challenge lies in the variation of object categories and scenes. Additionally, specialized datasets focus on specific categories. The second challenge involves novel category discrimination.

Deep Learning 95

Deep Learning ML AI Researcher AI Research 95

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. However, the image segmentation domain consists of various categories.

Computer Vision 98

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 98

Viso.ai

FEBRUARY 11, 2024

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. The hierarchy is composed of nodes that define the categories.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 52

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.

Machine Learning 107

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 107

AI Weekly

SEPTEMBER 14, 2023

apnews.com Applied use cases DO’s and DON’Ts of AI and LLMs for Hotels Deep learning: A subset of machine learning that uses multi-layered neural networks to model and process complex data representations, enabling AI systems to learn and adapt continuously from vast amounts of data. 2007, Rees et al.

Robotics 218

Robotics Artificial Intelligence Artificial Intelligence Machine Learning 218

PyImageSearch

FEBRUARY 6, 2023

Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g., If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. tomato, brinjal, and bottle gourd).

Auto-classification 144

Auto-classification Computer Vision Neural Network Deep Learning 144

IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Neural Network 150

Neural Network Deep Learning Machine Learning Artificial Intelligence 150

AWS Machine Learning Blog

APRIL 5, 2024

It’s based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. It requires no machine learning (ML) expertise to use and we’re continually adding new computer vision features to the service.

Computer Vision 101

Computer Vision Machine Learning Deep Learning Artificial Intelligence 101

Marktechpost

APRIL 24, 2024

Key innovations of SHAP include (1) the discovery of a new category of additive feature importance measures and (2) theoretical findings that demonstrate a distinct solution within this category that possesses a collection of favorable properties.

Explainable AI 110

Explainable AI Explainability Neural Network Data Scientist 110