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.

Convolutional Neural Networks 117

Convolutional Neural Networks Neural Network Deep Learning Algorithm 117

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?

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Computer Vision 52

AI Weekly

NOVEMBER 23, 2023

forbes.com Applied use cases From Data To Diagnosis: A Deep Learning Approach To Glaucoma Detection When the algorithm is implemented in clinical practice, clinicians collect data such as optic disc photographs, visual fields, and intraocular pressure readings from patients and preprocess the data before applying the algorithm to diagnose glaucoma.

Convolutional Neural Networks 258

Convolutional Neural Networks Neural Network OpenAI Robotics 258

Marktechpost

FEBRUARY 12, 2024

Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. As a result, many people are interested in finding ways to maximize the energy efficiency of DNNs through algorithm and hardware optimization. There are three notable characteristics of PDC in general.

Convolutional Neural Networks 132

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 132

Analytics Vidhya

DECEMBER 14, 2020

Introduction: Hi everyone, recently while participating in a Deep Learning competition, I. The post An Approach towards Neural Network based Image Clustering appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Neural Network 392

Neural Network Deep Learning Data Science Convolutional Neural Networks 392

Unite.AI

JULY 23, 2024

Once the brain signals are collected, AI algorithms process the data to identify patterns. These algorithms map the detected patterns to specific thoughts, visual perceptions, or actions. For instance, in visual reconstructions, the AI system learns to associate brain wave patterns with images a person is viewing.

Convolutional Neural Networks 317

Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 317

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.

Deep Learning 137

Deep Learning Convolutional Neural Networks Neural Network Natural Language Processing 137

Unite.AI

NOVEMBER 6, 2023

Traditional machine learning is a broad term that covers a wide variety of algorithms primarily driven by statistics. The two main types of traditional ML algorithms are supervised and unsupervised. These algorithms are designed to develop models from structured datasets. K-means Clustering. K-means Clustering.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

AI Weekly

SEPTEMBER 12, 2024

techcrunch.com Algorithm sharpens facial features for better emotion detection New research introduces a method to improve the accuracy and speed of dynamic emotion recognition using a convolutional neural network (CNN) to analyze faces. Register now dotai.io update and beyond.

Convolutional Neural Networks 264

Convolutional Neural Networks Robotics Neural Network Artificial Intelligence 264

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.

Convolutional Neural Networks 261

Convolutional Neural Networks Robotics Artificial Intelligence Artificial Intelligence 261

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. However, ensuring the understandability of complex algorithms to ornithologists and biologists is essential.

Deep Learning 107

Deep Learning Convolutional Neural Networks Neural Network Algorithm 107

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.

Deep Learning 104

Deep Learning Machine Learning Algorithm Convolutional Neural Networks 104

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 113

Deep Learning Convolutional Neural Networks Neural Network Computer Vision 113

Marktechpost

JANUARY 15, 2025

This gap has led to the evolution of deep learning models, designed to learn directly from raw data. What is Deep Learning? Deep learning, a subset of machine learning, is inspired by the structure and functioning of the human brain. High Accuracy: Delivers superior performance in many tasks.

Deep Learning 87

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 87

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?

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

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.

Deep Learning 111

Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

Flipboard

NOVEMBER 5, 2024

It aimed to analyze the value of deep learning algorithm combined with magnetic resonance imaging (MRI) in the risk diagnosis and prognosis of endometrial cancer (EC).

Convolutional Neural Networks 136

Convolutional Neural Networks Artificial Intelligence Artificial Intelligence Neural Network 136

Heartbeat

FEBRUARY 6, 2023

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. In the second step, these potential fields are classified and corrected by the neural network model.

Algorithm 90

Algorithm Convolutional Neural Networks Neural Network Computer Vision 90

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.

Deep Learning 87

Deep Learning Convolutional Neural Networks Neural Network Computer Vision 87

Marktechpost

SEPTEMBER 24, 2024

Previously, researchers doubted that neural networks could solve complex visual tasks without hand-designed systems. However, this work demonstrated that with sufficient data and computational resources, deep learning models can learn complex features through a general-purpose algorithm like backpropagation.

Convolutional Neural Networks 62

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 62

Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications. Howard et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

Deep Learning 52

Deep Learning Convolutional Neural Networks Algorithm Neural Network 52

Marktechpost

NOVEMBER 20, 2024

Others have proposed a hybrid network intrusion detection system integrating convolutional neural networks (CNN), fuzzy C-means clustering, genetic algorithm, and a bagging classifier. This research demonstrates the powerful potential of deep learning in enhancing intrusion detection systems against DDoS attacks.

Deep Learning 83

Deep Learning Convolutional Neural Networks Neural Network Algorithm 83

Marktechpost

JUNE 3, 2024

Its AI courses offer hands-on training for real-world applications, enabling learners to effectively use Intel’s portfolio in deep learning, computer vision, and more. Introduction to Machine Learning This course covers machine learning basics, including problem-solving, model building, and key algorithms.

Convolutional Neural Networks 122

Convolutional Neural Networks Neural Network Deep Learning Computer Vision 122

Chatbots Life

MAY 16, 2024

IF THERE IS A SIN, THIS IS THE ONLY SIN; TO SAY THAT YOU ARE WEAK, OR OTHERS ARE WEAK” - By Swami Vivekanand Is Deep Learning now overtaking the Machine Learning algorithm? Let us first know what is Machine Learning ? Machine Learning was coined by “ Arthur Samuel ” in the year 1959. Must Watch.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Marktechpost

MAY 5, 2024

Machine Learning with Python This course covers the fundamentals of machine learning algorithms and when to use each of them. Machine Learning Specialization “Machine Learning Specialization” teaches the core concepts of machine learning and how to build real-world AI applications using the same.

Machine Learning 120

Machine Learning Python Neural Network Convolutional Neural Networks 120

Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. How Deep Learning Algorithms Work?

Deep Learning 52

Deep Learning Machine Learning Algorithm Neural Network 52

Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! How Does Image Classification Work?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Marktechpost

MAY 26, 2024

Designing and deploying these systems requires a comprehensive hardware-software co-design toolchain that optimizes across devices, circuits, and algorithms. HW-NAS for IMC integrates four deep learning techniques: model compression, neural network model search, hyperparameter search, and hardware optimization.

Neural Network 130

Neural Network Convolutional Neural Networks Deep Learning Automation 130

PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

Convolutional Neural Networks 113

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 113

NVIDIA

OCTOBER 26, 2023

Researchers are taking deep learning for a deep dive, literally. The paper describes a model, called DeepSeeColor, that uses a sequence of two convolutional neural networks to reduce backscatter and correct colors in real time on the NVIDIA Jetson Orin NX while undersea.

Robotics 115

Robotics Deep Learning Convolutional Neural Networks Neural Network 115

Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. The recent deep learning algorithms provide robust person detection results. Most modern person detector techniques are trained on frontal and asymmetric views.

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Unite.AI

OCTOBER 22, 2024

This term refers to how much time, memory, or processing power an algorithm requires as the size of the input grows. 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.

Neural Network 147

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 147

Viso.ai

OCTOBER 9, 2024

Human-machine interaction is an important area of research where machine learning algorithms with visual perception aim to gain an understanding of human interaction. State-of-the-art emotion AI Algorithms Outlook, current research, and applications What Is AI Emotion Recognition? About us: Viso.ai What is Emotion AI?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Emotion AI 98

Viso.ai

DECEMBER 3, 2023

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. Today, the most powerful image processing models are based on convolutional neural networks (CNNs). Definition: What is pose estimation?

Deep Learning 98

Deep Learning Computer Vision Neural Network Robotics 98

Heartbeat

NOVEMBER 14, 2023

Integrating XGboost with Convolutional Neural Networks Photo by Alexander Grey on Unsplash XGBoost is a powerful library that performs gradient boosting. It has an excellent reputation as a tool for predicting many kinds of problems in data science and machine learning. It was envisioned by Thongsuwan et al.,

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Towards AI

JULY 9, 2024

Advances in artificial intelligence and machine learning have led to the development of increasingly complex object detection algorithms, which allow us to efficiently and precisely interpret large volumes of geographical data. This is somewhat of a popular algorithm for geospatial analysis. What is Object Detection?

Convolutional Neural Networks 109

Convolutional Neural Networks ML Neural Network Computer Vision 109