Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. Deep learning and AI technologies play crucial roles in both modular and End2End systems for autonomous driving. Classical methodologies for these tasks are also explored.

Deep Learning 122

Deep Learning Neural Network Data Scarcity Natural Language Processing 122

Flipboard

MARCH 17, 2025

Understanding Query Parameters Query parameters allow users to send additional information as part of the URL. Path parameters are used when the URL needs to include dynamic information, such as an ID or a name. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

Python 153

Python Computer Vision Auto-complete Deep Learning 153

AssemblyAI

DECEMBER 7, 2023

A joint audio-language model trained on suitably expansive datasets of audio and text could learn more universal representations to transfer robustly across both modalities.    This problem is harder for audio because audio data is far more information-dense than text.

Explainability 278

Explainability Large Language Models AI AI 278

NVIDIA

JANUARY 6, 2025

NVIDIA GPUs and platforms are at the heart of this transformation, Huang explained, enabling breakthroughs across industries, including gaming, robotics and autonomous vehicles (AVs). The latest generation of DLSS can generate three additional frames for every frame we calculate, Huang explained.

Robotics 144

Robotics Explainability AI AI 144

PyImageSearch

DECEMBER 9, 2024

Citation Information 3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction? In this tutorial, you will learn about 3D Gaussian Splatting. This lesson is the last of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion NeRFs Explained: Goodbye Photogrammetry?

Computer Vision 105

Computer Vision Deep Learning Explainability Algorithm 105

Unite.AI

JUNE 25, 2023

In a significant breakthrough, the UCLA study intends to combine the deep understanding from data and the real-world know-how of physics, thereby creating a hybrid AI with augmented capabilities.

Computer Vision 361

Computer Vision Robotics Neural Network Hybrid AI 361

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 126

Explainability Explainable AI Neural Network Algorithm 126

Towards AI

SEPTEMBER 10, 2023

What I’ve learned from the most popular DL course Photo by Sincerely Media on Unsplash I’ve recently finished the Practical Deep Learning Course from Fast.AI. So you definitely can trust his expertise in Machine Learning and Deep Learning. Luckily, there’s a handy tool to pick up Deep Learning Architecture.

Deep Learning 124

Deep Learning Neural Network ML Computer Vision 124

PyImageSearch

OCTOBER 28, 2024

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?

Explainability 103

Explainability Neural Network Computer Vision Deep Learning 103

Marktechpost

NOVEMBER 29, 2023

While classical cognitive models explain many psychological features of speech perception, these models fall short in explaining brain coding and natural speech recognition. Deep learning models are getting close to human performance in automated speech recognition.

Deep Learning 113

Deep Learning Neural Network Explainability AI Modeling 113

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

Marktechpost

MARCH 31, 2024

Solving partial differential equations (PDEs) is complex, just like the events they explain. Deep learning, using designs like U-Nets, is popular for working with information at multiple levels of detail. Earlier methods of solving these equations struggled with the challenge of changes happening over time.

Deep Learning 135

Deep Learning Explainability ML Artificial Intelligence 135

AWS Machine Learning Blog

APRIL 7, 2025

Dynamic content, including user-specific information, should be placed at the end of the prompt. n - Select quotes that provide key information, context, or support for the answer." n - Provide a clear, concise, and accurate answer to the question based on the information in the document." "n 2][3]'" "nn5.

Generative AI 126

Generative AI Explainability IDP LLM 126

Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. We will explain intuitively what each one means and how it contributes to the deep learning process.

Deep Learning 126

Deep Learning Neural Network Natural Language Processing Machine Learning 126

PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? To learn about 3D Reconstruction, just keep reading. 3D Gaussian Splatting: The End Game of 3D Reconstruction?

Explainability 117

Explainability Computer Vision Deep Learning Algorithm 117

Flipboard

FEBRUARY 10, 2025

Multimodal Capabilities in Detail Configuring Your Development Environment Project Structure Implementing the Multimodal Chatbot Setting Up the Utilities (utils.py) Designing the Chatbot Logic (chatbot.py) Building the Interface (app.py) Summary Citation Information Building a Multimodal Gradio Chatbot with Llama 3.2 Introducing Llama 3.2

Chatbots 149

Chatbots Computer Vision Deep Learning Large Language Models 149

Marktechpost

JANUARY 28, 2024

These studies, while informative, face significant limitations due to the high-dimensional nature of genotypes and the intricate, non-linear interactions of genetic components in determining an organism’s fitness. A researcher from the University of Zurich has turned to deep learning as a potent tool.

Explainability 119

Explainability Deep Learning Neural Network Machine Learning 119

IBM Journey to AI blog

AUGUST 9, 2024

Most generative AI models start with a foundation model , a type of deep learning model that “learns” to generate statistically probable outputs when prompted. In short, predictive AI helps enterprises make informed decisions regarding the next step to take for their business.

Generative AI 301

Generative AI Explainability AI AI 301

PyImageSearch

JANUARY 20, 2025

This results in a significant reduction in the overall size of the data without any loss of information, making Huffman encoding an essential tool in the realm of data compression. By encoding data based on the frequency of occurrence, it achieves compression without any loss of information.

Computer Vision 109

Computer Vision Deep Learning Explainability Algorithm 109

Unite.AI

MARCH 20, 2025

Seamlessly integrated with third party digital pathology software solutions, scanning platforms and laboratory information systems, Ibexs AI-enabled workflows deliver automated high-quality insights that enhance patient safety, increase physician confidence and boost productivity.

Convolutional Neural Networks 147

Convolutional Neural Networks Algorithm Explainability Neural Network 147

PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

Computer Vision 101

Computer Vision Deep Learning Neural Network Artificial Intelligence 101

Unite.AI

JULY 26, 2024

LLMs excel in advanced natural language processing (NLP) tasks, automated content generation, intelligent search, information retrieval, language translation, and personalized customer interactions. These AI models learn from huge datasets using deep learning techniques.

ChatGPT 281

ChatGPT OpenAI Natural Language Processing NLP 281

Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Is Deep Learning just another name for AI? Is all AI Deep Learning?

Deep Learning 52

Deep Learning Artificial Intelligence Artificial Intelligence Explainability 52

Marktechpost

NOVEMBER 30, 2023

Researchers from Lund University and Halmstad University conducted a review on explainable AI in poverty estimation through satellite imagery and deep machine learning. The review underscores the significance of explainability for wider dissemination and acceptance within the development community.

Deep Learning 98

Deep Learning AI Researcher AI Research Neural Network 98

AI Weekly

APRIL 11, 2024

And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses. Answering them, he explained, requires an interdisciplinary approach.

Robotics 264

Robotics Artificial Intelligence Artificial Intelligence Data Drift 264

Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

Marktechpost

JULY 22, 2024

With deep learning models like BERT and RoBERTa, the field has seen a paradigm shift. This lack of explainability is a gap in academic interest and a practical concern. Existing methods for AV have advanced significantly with the use of deep learning models.

Explainability 104

Explainability BERT Large Language Models Deep Learning 104

Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Explainability is essential for accountability, fairness, and user confidence. Explainability also aligns with business ethics and regulatory compliance.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182

Unite.AI

DECEMBER 1, 2023

Exploring the Techniques of LIME and SHAP Interpretability in machine learning (ML) and deep learning (DL) models helps us see into opaque inner workings of these advanced models. Risks with Personal Data LLMs require extensive training data, which may include sensitive personal information.

LLM 264

LLM Machine Learning Explainability Algorithm 264

AWS Machine Learning Blog

MARCH 21, 2025

Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data. samples/2003.10304/page_5.png"

Metadata 111

Metadata Convolutional Neural Networks Generative AI Data Scientist 111

PyImageSearch

DECEMBER 16, 2024

For more information, head over to Fine Tune PaliGemma with QLoRA for Visual Question Answering. The debug=True option enables debugging information, which can be helpful for troubleshooting. Document Understanding involves analyzing images that contain both visual elements and textual information.

Computer Vision 100

Computer Vision Deep Learning Artificial Intelligence Artificial Intelligence 100

IBM Journey to AI blog

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. All this reduces the risk of a data leak or unauthorized access.

Large Language Models 289

Large Language Models LLM Explainability Chatbots 289

Towards AI

FEBRUARY 6, 2025

to Artificial Super Intelligence and black box deep learning models. It details the underlying Transformer architecture, including self-attention mechanisms, positional embeddings, and feed-forward networks, explaining how these components contribute to Llamas capabilities. Enjoy the read!

Deep Learning 72

Deep Learning Computer Vision Large Language Models Explainability 72

PyImageSearch

DECEMBER 23, 2024

These word vectors are trained from Twitter data making them semantically rich in information. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Here youll learn how to successfully and confidently apply computer vision to your work, research, and projects.

Computer Vision 107

Computer Vision Algorithm Deep Learning Metadata 107

PyImageSearch

JANUARY 13, 2025

This task is particularly useful when the goal is to identify the category of an image without needing information about the location or shape of specific objects within it. This file contains the necessary information about the dataset (e.g., YOLO11 image classification models are pre-trained on the ImageNet dataset.

Computer Vision 101

Computer Vision Python Deep Learning Neural Network 101

Marktechpost

MARCH 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 142

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 142

Marktechpost

NOVEMBER 20, 2024

The Semantic Re-encoding Deep Learning Model (SRDLM) can also be used to improve traffic distinguishability and algorithmic generalization, as presented by the prior researchers. By hybridizing optimization techniques with deep belief networks, the method aims to enhance DDoS attack detection accuracy, speed, and scalability.

Deep Learning 83

Deep Learning Convolutional Neural Networks Neural Network Algorithm 83