NVIDIA

JUNE 23, 2023

The geoglyphs — a humanoid, a pair of legs, a fish and a bird — were revealed using a deep learning model, making the discovery process significantly faster than traditional archaeological methods. The team’s deep learning model training was executed on an IBM Power Systems server with an NVIDIA GPU. Read the full paper.

Deep Learning 118

Deep Learning Categorization AI AI 118

Marktechpost

JULY 30, 2024

Researchers from Stanford University, Kumo.AI, and the Max Planck Institute for Informatics introduced RelBench , a groundbreaking benchmark to facilitate deep learning on relational databases. This initiative aims to standardize the evaluation of deep learning models across diverse domains and scales.

Deep Learning 122

Deep Learning Neural Network Categorization Data Extraction 122

Analytics Vidhya

JULY 20, 2022

Two popular types of categorization techniques are […]. Introduction Image classification is the process of classifying and recognizing groups of pixels inside an image in line with pre-established principles. Using one or more spectral or text qualities is feasible while creating the classification regulations.

Categorization 374

Categorization Data Science Computer Vision Deep Learning 374

Marktechpost

JULY 13, 2024

According to their cost-volume computation and optimization methodologies, existing surveys categorize end-to-end architectures into 2D and 3D classes. New approaches and paradigms have emerged in the field since then, spurred by innovations in other branches of deep learning, and the domain has seen tremendous growth since then.

Deep Learning 110

Deep Learning Computer Vision Categorization Robotics 110

Marktechpost

JANUARY 14, 2024

There has been a meteoric rise in the use of deep learning in image processing in the past several years. The robust feature learning and mapping capabilities of deep learning-based approaches enable them to acquire intricate blur removal patterns from large datasets.

Deep Learning 115

Deep Learning Convolutional Neural Networks Neural Network Computer Vision 115

Marktechpost

SEPTEMBER 4, 2023

Researchers also categorized the type of spine curve just by looking at one picture. The post This AI Paper Presents a Study on AIS (Androgen Insensitivity Syndrome) Testing Using Deep Learning Models appeared first on MarkTechPost. These programs might reduce the need for X-rays in people with mild spine problems.

Deep Learning 126

Deep Learning Computer Vision Categorization AI 126

Unite.AI

JUNE 2, 2023

Based on this, it makes an educated guess about the importance of incoming emails, and categorizes them into specific folders. In addition to the smart categorization of emails, SaneBox also comes with a feature named SaneBlackHole, designed to banish unwanted emails.

Categorization 261

Categorization Natural Language Processing Automation AI 261

Marktechpost

DECEMBER 3, 2023

PepCNN, a deep learning model developed by researchers from Griffith University, RIKEN Center for Integrative Medical Sciences, Rutgers University, and The University of Tokyo, addresses the problem of predicting protein-peptide binding residues. These advancements highlight the effectiveness of the proposed method.

Deep Learning 111

Deep Learning Categorization AI Researcher AI Research 111

Analytics Vidhya

JUNE 26, 2023

They allow the network to focus on different aspects of complex input individually until the entire data set is categorized. This approach […] The post Learn Attention Models From Scratch appeared first on Analytics Vidhya. The goal is to break down complex tasks into smaller areas of attention that are processed sequentially.

Neural Network 305

Neural Network Categorization Deep Learning NLP 305

IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

ESG 238

ESG Categorization Large Language Models NLP 238

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 model, trained on a substantial dataset, performs strongly in categorizing macula-centered 3D volumes into Normal, iAMD, GA, and nAMD stages.

Deep Learning 111

Deep Learning Convolutional Neural Networks Neural Network Categorization 111

ODSC - Open Data Science

APRIL 28, 2023

In this post, I’ll be demonstrating two deep learning approaches to sentiment analysis. Deep learning refers to the use of neural network architectures, characterized by their multi-layer design (i.e. deep” architecture). These can be customized and trained. We’ll be mainly using the “.cats”

Deep Learning 98

Deep Learning Convolutional Neural Networks Neural Network NLP 98

Unite.AI

SEPTEMBER 18, 2023

Blockchain technology can be categorized primarily on the basis of the level of accessibility and control they offer, with Public, Private, and Federated being the three main types of blockchain technologies. Deep learning frameworks can be classified into two categories: Supervised learning, and Unsupervised learning.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

AI Weekly

OCTOBER 12, 2023

techspot.com Applied use cases Study employs deep learning to explain extreme events Identifying the underlying cause of extreme events such as floods, heavy downpours or tornados is immensely difficult and can take a concerted effort by scientists over several decades to arrive at feasible physical explanations. [Get your FREE REPORT.]

Robotics 239

Robotics Large Language Models Deep Learning Artificial Intelligence 239

Marktechpost

MARCH 11, 2024

This obstacle sharply differs from supervised learning, where leveraging cross-entropy classification loss enables reliable scaling to vast networks. In deep learning, classification tasks show effectiveness with large neural networks, while regression tasks can benefit from reframing as classification, enhancing performance.

Neural Network 129

Neural Network Categorization Deep Learning Robotics 129

Marktechpost

APRIL 5, 2024

The proposed approach was explained by analyzing neural network architectures, particularly transformers, from a categorical perspective, specifically utilizing topos theory. While traditional neural networks can be embedded in pretopos categories, transformers necessarily reside in a topos completion.

Neural Network 128

Neural Network Natural Language Processing Categorization Explainability 128

SAS Software

SEPTEMBER 7, 2023

Using digital images from cameras and videos and deep learning models, machines can learn to recognize and categorize objects and respond to their surroundings based on what they “see.” Computer vision is a field of artificial intelligence that teaches computers to understand visuals.

Computer Vision 116

Computer Vision Categorization Deep Learning Artificial Intelligence 116

John Snow Labs

JUNE 2, 2023

Sentiment analysis, also known as opinion mining, is the process of computationally identifying and categorizing the subjective information contained in natural language text. Deep learning models can automatically learn features and representations from raw text data, making them well-suited for sentiment analysis tasks.

Deep Learning 76

Deep Learning NLP Convolutional Neural Networks Neural Network 76

Marktechpost

MAY 3, 2024

This interdisciplinary field incorporates linguistics, computer science, and mathematics, facilitating automatic translation, text categorization, and sentiment analysis. Sparse retrieval employs simpler techniques like TF-IDF and BM25, while dense retrieval leverages deep learning to improve accuracy.

Natural Language Processing 138

Natural Language Processing Large Language Models Categorization BERT 138

The MLOps Blog

MARCH 1, 2024

TL;DR Deep learning models exhibit excellent performance but require high computational resources. Deep learning models continue to dominate the machine-learning landscape. Training and operating the deep learning models is expensive and time-consuming and has a significant impact on the environment.

Deep Learning 59

Deep Learning Neural Network Categorization Machine Learning 59

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters.

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

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. It is also widely used in solving inverse imaging problems, such as image denoising and super-resolution imaging.

Neural Network 115

Neural Network Deep Learning Data Mining Natural Language Processing 115

Heartbeat

OCTOBER 11, 2023

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach.

Deep Learning 52

Deep Learning Machine Learning Neural Network Natural Language Processing 52

Heartbeat

FEBRUARY 21, 2024

Photo by Almos Bechtold on Unsplash Deep learning is a machine learning sub-branch that can automatically learn and understand complex tasks using artificial neural networks. Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns.

Deep Learning 52

Deep Learning Neural Network Machine Learning Algorithm 52

Unite.AI

MAY 29, 2024

With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text. Subsequently, some RNNs were also trained using GPUs, though they did not yield good results.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

Heartbeat

NOVEMBER 14, 2023

For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. XGBoost is not limited to machine learning tasks, as its incredible power can be harnessed when harmonized with deep learning algorithms. " Nuclear Engineering and Technology 53, no.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Marktechpost

DECEMBER 22, 2023

Researchers from Lebanese American University and United Arab Emirates University have collaborated to employ artificial intelligence (AI) successfully through the Scale Conjugate Gradient Neural Network (SCJGNN), providing numerical solutions for the language-based learning model. If you like our work, you will love our newsletter.

Deep Learning 59

Deep Learning Categorization Neural Network Artificial Intelligence 59

Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. It is a tremendous tool with the ability to completely alter numerous sectors.

Software Development 52

Software Development Deep Learning Neural Network Convolutional Neural Networks 52

Marktechpost

NOVEMBER 16, 2024

They used the Credit Risk dataset, from which they generated synthetic data using deep learning models (TVAE, CTGAN, CopulaGAN) and differential privacy models (Independent, PrivBayes, DPsynthpop) to create 102 synthetic variants. In contrast, deep learning models produced higher-quality data but had more outliers.

Deep Learning 111

Deep Learning Data Quality Categorization Machine Learning 111

Marktechpost

APRIL 26, 2024

Graph Machine Learning (Graph ML), especially Graph Neural Networks (GNNs), has emerged to effectively model such data, utilizing deep learning’s message-passing mechanism to capture high-order relationships. Alongside topological structure, nodes often possess textual features providing context.

Large Language Models 137

Large Language Models Machine Learning Neural Network Deep Learning 137

Marktechpost

DECEMBER 24, 2023

As the demand for sustainable agriculture grows, machine learning emerges as a vital force, reshaping the future of food security and cultivation. These methods address the challenges of traditional approaches, offering more automated, accurate, and robust solutions for identifying and categorizing plant leaf diseases.

Machine Learning 121

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 121

Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience.

Auto-complete 240

Auto-complete ChatGPT Large Language Models Neural Network 240

Marktechpost

JULY 18, 2024

Recognizing this limitation, the field of geometric deep learning has emerged, which seeks to extend classical machine learning techniques to non-Euclidean domains by utilizing geometric, topological, and algebraic structures.

Machine Learning 135

Machine Learning Computer Vision Neural Network Deep Learning 135

Marktechpost

SEPTEMBER 1, 2023

Artificial intelligence’s allure has long been shrouded in mystique, especially within the enigmatic realm of deep learning. The empirical law of equi-separation cuts through the apparent chaos, revealing an underlying order within deep neural networks. This revelation holds profound implications.

Neural Network 115

Neural Network Deep Learning Categorization Artificial Intelligence 115

Unite.AI

AUGUST 13, 2023

Identifying & Flagging Hate Speech Using AI In the battle against hate speech, AI emerges as a formidable ally, with machine learning (ML) algorithms to identify and flag harmful content swiftly and accurately. To train AI models for accurate hate speech detection, supervised and unsupervised learning techniques are used.

AI 246

AI AI AI Modeling Categorization 246

IBM Journey to AI blog

AUGUST 28, 2023

Some common techniques include the following: Sentiment analysis : Sentiment analysis categorizes data based on the nature of the opinions expressed in social media content (e.g., It also automates tasks like information extraction and content categorization. positive, negative or neutral).

Convolutional Neural Networks 170

Convolutional Neural Networks Data Mining Categorization Machine Learning 170

Viso.ai

MARCH 26, 2024

The introduction of the Transformer model was a significant leap forward for the concept of attention in deep learning. Types of Attention Mechanisms Attention mechanisms are a vital cog in modern deep learning and computer vision models. Vaswani et al. without conventional neural networks.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52