technology

A collection of 98 posts

technology

How This Startup Using Object Detection For Safer Driving

Table of Contents 1. Introduction 2. Role of Computer Vision 3. About Nauto 4. Founders 5. How Nauto Uses Computer Vision 6. Conclusion Introduction The problem of real-time object detection for safer driving affects the transportation industry and any other industries that rely on vehicles for their operations. The problem

technology

Supervised vs. Unsupervised Learning: Choosing the Right Path for Your Data Analysis

Supervised learning uses labeled data for predictive tasks like spam filtering or credit scoring, while unsupervised learning explores unlabeled data to identify patterns, aiding applications such as customer segmentation and anomaly detection

dataset

Maximizing Data Ingestion Performance for High-Volume Data Sources

In 2020, 64 zettabytes of data were generated in total! According to estimates, this amount will climb to 180 zettabytes by 2025 as the number of individuals working from home increases. With important system sources like smartphones, power grids, stock markets, and healthcare integrating more data sources as storage capacity

technology

Labellerr: A self-hosted & secured data annotation platform

In the world of data science, efficient and accurate labeling of data is crucial to ensuring successful Machine Learning applications. While an array of online tools exist to make data labeling easier, they often involve managing multiple vendor relationships, hosting external datasets on an alien server environment with limited accessibilities,

technology

Leveraging YOLO Object Detection for Accurate and Efficient Visual Recognition

It’s become increasingly evident that the YOLO algorithm has revolutionized the way we think about algorithms, and is quickly becoming an essential tool for machine learning applications. By streamlining object detection through efficient deep neural networks, YOLO has shown us how powerful one can be when effectively leveraging both

technology

Data annotation outsourcing: A step-by-step guide

Are you working with image-based data and struggling to keep up with the workload? Image annotation is an important part of any machine learning project that deals with image or video data, helping to speed the model development process. Unfortunately, not everyone has the technical skills or time needed for

data annotation

The next big thing in data annotation

Data enthusiasts use a variety of datasets while creating ML models, carefully adjusting each one to the model's training needs. Robots can therefore recognize content that has been labelled in a wide range of understandable formats, including images, texts, and videos. In order to train their algorithms to

data annotation

How to super fast data annotations process with automation?

Lexi is a US-based data scientist and she is currently working on a data annotation project. She is looking for various methods to bring automation to data annotations. Let’s see what are the possible options for her. Data annotation is a critical process for capturing data that can provide

technology

What Is Image Enhancement & Its Effect On Machine Vision

Imagine trying to drive a car in dense fog. Your visibility is limited, making it hard to see what's ahead. Now, picture someone handing you a pair of glasses that cut through the fog, suddenly revealing the road and obstacles clearly. This is what image enhancement does in

technology

How Dall-E and stable diffusion will automate our work in future?

The further adoption of both AI and automation technologies has been on the rise over several years, with more organizations looking to use automated systems as a way to improve efficiency, reduce costs and increase accuracy. This also means that we should take time to look at recent advances in

technology

Understand the tech: Stable diffusion vs GPT-3 vs Dall-E

The world of Artificial Intelligence (AI) is rapidly innovating with the development of new algorithms, models, and techniques. But how do you decide which AI technology to use? To help you in that decision-making process, we'll look at the differences between two of today's popular AI

technology

Top Machine Learning Projects to Build Your Skills

You have been learning programming languages, honing your machine-learning skills, and delving into the details of data points. Additionally, rather than just studying machine learning models, you are interested in creating your own. Machine learning (ML) projects provide you a chance to put your newly acquired skills to use while

technology

MLOps: What It Is? How to apply MLOps to Computer Vision?

It is challenging to operationalize machine learning to generate business benefits. It is challenging to convert models created using machine learning (ML) and artificial intelligence (AI) into dependable, scalable software that adds value to businesses. Companies are becoming increasingly engaged in using DevOps techniques for software that uses machine learning

technology

What are adversarial attacks in machine learning and how to prevent them?

Adversarial attacks in ML manipulate input data to mislead models, affecting fields like image recognition and spam detection. Learn how techniques like MLOps, secure ML practices, and data validation can defend against these evolving security threats.

technology

9 Capabilities Of DALL-E That One Must Know

DALL-E can generate imaginative, high-quality images by combining visual ideas and applying attributes like 3D perspectives and contextual details. With capabilities in artistic, realistic rendering, and visual reasoning, it transforms text prompts into diverse images.

technology

Math behind GAN (generative adversarial networks) & its applications

A generative model G and a discriminative model D make up the Generative Adversarial Network (GAN). The discriminative model is comparable to the police seeking to seize counterfeit money, but the generative model might be compared to a forger trying to create phony money and utilize it without being discovered.

technology

Unleashing the Power of ChatGPT: Revolutionizing Conversational AI

This technology is the current talk of the town. Not just AI Industry but almost every industry is talking about this new technology named as ChatGpt (a product by OpenAI). This technology is soon going to bring a different revolution in the industry. You may not have to go to

technology

How camera sensors help machine vision applications?

Camera sensors are light-sensitive detectors that convert incident photons into an electrical signal that can be read by a digital device. Most cameras use 2D array detectors, and choosing the right sensor for a given application is often a trade-off between cost, desired final image resolution, and required readout speed.

technology

What's GAN (generative adversarial networks), how it works?

Generative Adversarial Networks (GANs) involve two neural networks—a generator and a discriminator—competing to produce realistic data. Widely used in deep learning, GANs create images, predict frames, and transform visual styles, enhancing AI's creative applications.

technology

How an AI-powered smart city will manage its traffic in future

Vehicle “Idling” refers to running a vehicle’s engine when it’s not moving, such as when you’re at a red light or stuck in traffic. Idling is part of the process of driving a car and is a fairly common occurrence for most drivers. However, idling may not

technology

5 Image Data Augmentation Techniques To Mitigate Overfitting In Computer Vision

Deep Convolutional Neural networks have been shown to be effective for a variety of computer vision applications in a variety of fields, including autonomous vehicles, medical imaging, etc. However, in order for these networks to function exceptionally well in real-world situations, they greatly rely on big quality data. But how

technology

Taking the world by simulation: The rise of synthetic data in AI

According to survey results, 96% of teams claim to use synthetic data in some capacity for developing computer vision models. It's interesting to note that 81% of respondents said they use synthetic data in quantities at least equivalent to those of manual data. The essence of modern technology

technology

Object tracking in autonomous vehicles: How it works?

Autonomous vehicles (AVs) have received immense attention in recent years due to their potential to improve driving comfort and reduce injuries from vehicle crashes as human error is the key reason for more than 94% of accidents. Autonomous driving has moved from the realm of science fiction to a very

technology

Multi-View 3D reconstruction in autonomous vehicles, How it works?

Since the autonomous driving industry got its start at the 2005 DARPA Grand Challenge, numerous companies have trained and tested machine learning models to control every aspect of autonomous driving. The market leaders are continually updating and improving their ensembles of computer vision and control systems models to build safer,

technology

What is data augmentation? Techniques, examples & benefits

Data augmentation enhances machine learning models by creating varied data versions, boosting accuracy, and reducing data collection costs. Common in image recognition and NLP, it leverages techniques like GANs, word swaps, and neural style transfer