Unite.AI

DECEMBER 11, 2024

Understanding Neural Radiance Fields NeRFs are a significant development in computer vision and 3D rendering. Unlike traditional methods that depend on manually creating geometry and textures, NeRFs use deep learning to map how light and color interact in 3D space.

Neural Network 190

Neural Network Computer Vision Automation Deep Learning 190

Unite.AI

MAY 4, 2025

It uses deep learning , NLP, spatial computing, and system integration to extract meaningful data accurately and efficiently. At the core of Agentic Document Extraction are deep learning models trained on large amounts of data from both structured and unstructured documents.

Automation 230

Automation Convolutional Neural Networks Neural Network NLP 230

Unite.AI

MAY 14, 2025

Sylvester.ai : Asmartphone-based tool that uses computer vision and artificial intelligence to assess pain in cats by analyzing facial expressions. Preprocessing Faces are auto-detected and normalized for lighting, angle, and scale using computer vision techniques such as OpenCV-based alignment and histogram equalization.

Convolutional Neural Networks 144

Convolutional Neural Networks Computer Vision Artificial Intelligence Artificial Intelligence 144

PyImageSearch

DECEMBER 9, 2024

And in the 2nd blog of this series , you were introduced to NeRFs, which is 3D Reconstruction via Neural Networks, projecting points in the 3D space. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Join me in computer vision mastery.

Computer Vision 116

Computer Vision Deep Learning Explainability Algorithm 116

PyImageSearch

JULY 7, 2025

Limitations of YOLOv8 to YOLOv11 Despite these advancements, YOLOv8 through YOLOv11 shared common limitations: CNN-Centric Architectures: All models relied heavily on convolutional neural networks (CNNs) without integrating attention mechanisms. Or requires a degree in computer science? Join me in computer vision mastery.

Computer Vision 117

Computer Vision Python Deep Learning Convolutional Neural Networks 117

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

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

Unite.AI

APRIL 8, 2025

A Legacy Written in Code Canadas roots in AI date back to the 1980s, when Geoffrey Hinton arrived at the University of Toronto , supported by early government grants that allowed unconventional work on neural networks. These seemingly isolated efforts converged decades later to kickstart the deep learning revolution.

Deep Learning 223

Deep Learning Artificial Intelligence Artificial Intelligence AI 223

How to Learn Machine Learning

MAY 9, 2025

Introduction to Deep Boltzman Machine or Machines Hello friends! Welcome back to How to Learn Machine Learning ! Sit back, relax, and enjoy as we dive into the awesome world of Deep Boltzman Machine (DBM). Deep Boltzman Machine explained What Is a Deep Boltzman Machine Anyway? Happy learning!

Neural Network 81

Neural Network Convolutional Neural Networks Natural Language Processing Deep Learning 81

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.

Convolutional Neural Networks 144

Convolutional Neural Networks Algorithm Neural Network Computer Vision 144

Towards AI

DECEMBER 16, 2024

From breakthroughs in large language models to revolutionary approaches in computer vision and AI safety, the research community has outdone itself. Vision Mamba Summary: Vision Mamba introduces the application of state-space models (SSMs) to computer vision tasks. And lets be real what a year it has been!

AI Researcher 111

AI Researcher AI Research Computer Vision Neural Network 111

How to Learn Machine Learning

MAY 7, 2025

In the world of AI, you might hear a lot of Machine Learning vs Deep Learning. Introduction to Deep Learning vs Machine Learning To a lot of people, the terms Deep Learning and Machine Learning seem like buzzwords in the AI world. What is Deep Learning?

Deep Learning 52

Deep Learning Machine Learning Neural Network Artificial Intelligence 52

Unite.AI

MARCH 2, 2025

From early neural networks to todays advanced architectures like GPT-4 , LLaMA , and other Large Language Models (LLMs) , AI is transforming our interaction with technology. For years, deep learning has relied on traditional dense layers, where every neuron in one layer is connected to every neuron in the next.

Deep Learning 155

Deep Learning Neural Network Automation AI 155

Towards AI

JULY 9, 2025

Fast forward a few years, and as deep learning explodes in popularity, NVIDIA creates cuDNN, a specialized library built on top of CUDA that’s specifically designed to make neural networks run faster than a caffeinated cheetah. While CUDA knows a little about everything, cuDNN knows EVERYTHING about neural networks.

Neural Network 56

Neural Network Deep Learning Computer Vision Python 56

PyImageSearch

JANUARY 13, 2025

To learn how to master YOLO11 and harness its capabilities for various computer vision tasks , just keep reading. With improvements in its design and training techniques, YOLO11 can handle a variety of computer vision tasks, making it a flexible and powerful tool for developers and researchers alike.

Computer Vision 109

Computer Vision Python Deep Learning Neural Network 109

Unite.AI

MAY 22, 2025

Conservationists are now using computer vision and satellite data to monitor animal populations at scale , without disturbing ecosystems. Drones equipped with machine learning software can identify species, track movement patterns, and flag signs of distress in real-time. AI is being used to fill in the blanks.

Computer Vision 144

Computer Vision Machine Learning Neural Network Natural Language Processing 144

Flipboard

JUNE 16, 2025

It is a deep neural network architecture raised to its highest exponent, consisting of a variety of components and layers like position-wise feed-forward networks and self-attention that together allow for efficient parallel processing and context-aware representation of input sequences.

Large Language Models 137

Large Language Models Explainability Natural Language Processing Prompt Engineer 137

Unite.AI

APRIL 6, 2025

Unlike conventional voice recognition systems, FreshAI employs deep learning models trained on thousands of real-world customer interactions. Using neural network-based entity recognition, it accurately maps spoken requests to menu items, even when customers use ambiguous phrasing or slang.

Automation 179

Automation AI AI Neural Network 179

Pickl AI

JUNE 2, 2025

Summary: Gradient-based learning optimizes machine learning models by iteratively minimizing errors using gradients of loss functions. Central to deep learning, it relies on gradient descent and learning rate tuning to train models efficiently across various applications, despite challenges like local minima and computational costs.

Machine Learning 52

Machine Learning Neural Network Natural Language Processing Convolutional Neural Networks 52

Flipboard

JUNE 13, 2025

Its extensive libraries, such as TensorFlow, PyTorch, and Scikit-learn, streamline the development of machine learning and deep learning models. Key areas of focus include: Linear Algebra: Essential for understanding data representation in AI models, such as vectors and matrices used in neural networks.

Artificial Intelligence 73

Artificial Intelligence Artificial Intelligence Neural Network Auto-complete 73

Bugra Akyildiz

FEBRUARY 26, 2025

Stanford CS224n: Natural Language Processing with Deep Learning Stanford’s CS224n stands as the gold standard for NLP education, offering a rigorous exploration of neural architectures, sequence modeling, and transformer-based systems. S191: Introduction to Deep Learning MIT’s 6.S191

Deep Learning 40

Deep Learning NLP Machine Learning Robotics 40

AWS Machine Learning Blog

JULY 11, 2025

P-tuning P-tuning extends prompt tuning by representing prompts as continuous embeddings passed through a small trainable neural network (typically an MLP). It’s particularly valuable for training resource-intensive models like LLMs and complex computer vision systems.

AI 77

AI AI Deep Learning LLM 77

Towards AI

MAY 18, 2025

AI algorithms, particularly deep learning and reinforcement learning models, play an important role. Computer Vision. Computer vision allows vehicles to identify and classify road signs, traffic lights, people, and lane markings. Sensor Fusion.

Convolutional Neural Networks 63

Convolutional Neural Networks Computer Vision Neural Network Artificial Intelligence 63

Pickl AI

DECEMBER 26, 2024

Key Features and Capabilities Ultracluster offers an unprecedented level of parallel computing, enabling seamless handling of exabytes of data. Its key features include distributed training at scale, optimised performance for deep learning frameworks, and real-time processing for complex tasks.

Natural Language Processing 52

Natural Language Processing Computer Vision Robotics Machine Learning 52

Marktechpost

MARCH 16, 2025

Stereo depth estimation plays a crucial role in computer vision by allowing machines to infer depth from two images. Despite advancements in deep learning , many existing stereo-matching models require domain-specific fine-tuning to achieve high accuracy.

Convolutional Neural Networks 82

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 82

Towards AI

DECEMBER 26, 2024

Urfavalm is developing an AI-based mobile app to help people with disabilities and is looking for one or two developers with experience in mobile app development and NLP or computer vision. is looking to collaborate with someone on an ML-based project deep learning, Pytorch. Shubhamgaur. Meme of the week!

LLM 105

LLM Neural Network NLP Computer Vision 105

Marktechpost

MARCH 20, 2025

Let’s create a small dataset of abstracts from various fields: Copy Code Copied Use a different Browser abstracts = [ { "id": 1, "title": "Deep Learning for Natural Language Processing", "abstract": "This paper explores recent advances in deep learning models for natural language processing tasks.

Natural Language Processing 55

Natural Language Processing Convolutional Neural Networks Neural Network Computer Vision 55

AWS Machine Learning Blog

MARCH 13, 2025

MoE models like DeepSeek-V3 and Mixtral replace the standard feed-forward neural network in transformers with a set of parallel sub-networks called experts. These experts are selectively activated for each input, allowing the model to efficiently scale to a much larger size without a corresponding increase in computational cost.

LLM 109

LLM Machine Learning AI AI 109

PyImageSearch

JUNE 23, 2025

They also exported the models to Open Neural Network Exchange (ONNX) format, enabling them to run on many platforms. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? That’s not the case.

Computer Vision 84

Computer Vision Deep Learning LLM Neural Network 84

Bugra Akyildiz

MAY 18, 2025

AXLearn is a library built on top of JAX and XLA to support the development of large-scale deep learning models. Our mission is to build intelligent GUI agents that can learn from past experiences and perform complex tasks autonomously on your computer.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network LLM 52

Unite.AI

FEBRUARY 8, 2025

Vision Transformers (ViTs) have significantly advanced computer vision by using attention mechanisms instead of the traditional convolutional layers. This change has allowed ViTs to outperform Convolutional Neural Networks (CNNs) in image classification and object detection tasks.

Convolutional Neural Networks 266

Convolutional Neural Networks Neural Network Natural Language Processing Robotics 266

Bugra Akyildiz

FEBRUARY 22, 2025

These limitations motivated the development of an embedding-based retrieval system that could learn representations directly from user engagement data, mirroring the success of deep learning in ranking systems.

LLM 59

LLM Metadata Large Language Models Artificial Intelligence 59

ML @ CMU

APRIL 23, 2025

Lee Other Topics In Machine Learning (I.e., Applications to Robotics, Autonomy, Planning Causal Reasoning Datasets and Benchmarks Foundation or Frontier Models, Including LLMs Generative Models Infrastructure, Software Libraries, Hardware, Systems, etc. Gordon, Fei Fang Physics of Language Models: Part 2.1,

Large Language Models 68

Large Language Models LLM Robotics Algorithm 68

ML @ CMU

JULY 8, 2025

Here is a quick overview of the areas our researchers are working on: Here are our most frequent collaborator institutions: Table of Contents Oral Papers Spotlight Papers Poster Papers Accountability, Transparency, And Interpretability Active Learning And Interactive Learning Applications Causality Chemistry, Physics, And Earth Sciences Computer Vision (..)

Large Language Models 85

Large Language Models LLM Neural Network Machine Learning 85

AssemblyAI

FEBRUARY 4, 2025

These Convolutional Neural Networks (CNNs) - particularly ResNet varieties - have revolutionized computer vision by treating images like a grid on which local spatial relationships can be learned. This kind of simultaneous improvement in both accuracy and efficiency is rare in deep learning research.

Neural Network 147

Neural Network Convolutional Neural Networks Deep Learning AI 147

Analytics Vidhya

DECEMBER 28, 2021

This article was published as a part of the Data Science Blogathon Source: Vision Image Overview Deep learning is the most powerful method used to work on vision-related tasks. Convolutional Neural Networks or convents are a type of deep learning model which we use to approach computer vision-related applications.

Computer Vision 395

Computer Vision Deep Learning Convolutional Neural Networks Neural Network 395

Analytics Vidhya

OCTOBER 4, 2021

Convolutional Neural Network is a type of deep learning neural network that is artificial. It is employed in computer vision and image recognition. The post Applications of Convolutional Neural Networks(CNN) appeared first on Analytics Vidhya.

Convolutional Neural Networks 387

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 387

Analytics Vidhya

FEBRUARY 10, 2020

Overview Convolutional neural networks (CNNs) are all the rage in the deep learning and computer vision community How does this CNN architecture work? The post Demystifying the Mathematics Behind Convolutional Neural Networks (CNNs) appeared first on Analytics Vidhya. We’ll.

Convolutional Neural Networks 343

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 343