technology

A collection of 45 posts

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

How YOLO algorithm helps in object detection?

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 recognize recurring

technology

Machine learning steps: A complete guide for beginner in ML

A machine learning system learns from historical data, builds a predictive model, and predicts its output whenever new data is obtained. The accuracy of the predicted output depends on the amount of data. Massive amounts of data help build better models that more accurately predict the output. Suppose you have

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

Semantic vs Instance vs Panoptic: Which Image Segmentation Technique To Choose?

The way machines carry out vision-based activities has altered as a result of image segmentation. For instance, just a few decades ago, object identification and prediction-based decision-making were difficult for machines. However, the development of computer vision models which can identify objects, recognize their shapes, forecast the direction in which

technology

What is image enhancement and how does it affect machine vision?

Image enhancement is a powerful tool that can be used to improve the visual quality of images and to equip machine vision systems with more accurate information. In its simplest form, image enhancement involves altering an image to make it appear clearer, sharper, and more visually appealing. By improving the

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 technologies: stable diffusion vs

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?

Several of the technologies users use daily now include machine learning, from the face detection security on iPhone to Alexa's voice recognition feature and the spam protection in our emails. However, the widespread use of machine learning and its variant, deep learning, has also sparked the emergence of adversarial assaults,

technology

Everything you need to know about DALL-E and more.

While there are other text-to-image systems (such as the tokens-based programmes VQGAN+CLIP and CLIP-Guided Diffusion, which are accessible on Night Cafe), the most recent version of DALL-E is significantly better at producing coherent images. The world and the connections between objects appear to be well understood by technology. DALL-E

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

ChatGPT: What is it? Why it's special?

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?

Have you ever considered transforming your zebra to horse or horse to zebra images? Have you ever considered foreseeing the following video frame? Imagine being able to create an image from a sentence. Would you like to create emojis using images? Do you want to make an image from various

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

How computer vision based ATTOL system helps air crafts in landing & takeoff

To use vision-based onboard camera sensors for detecting marked runway features and provide guidance to aircraft for aligning with runway central line and holding. Existing Methods: Pilots rely mostly on their eyes, skills or ATC (Air Traffic Controllers) for Landing ILS (Instrument Landing System) Installed Over Some Airports Auto landing

technology

Top 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 is quality

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 is the era's essential core. Every decision in the world is driven by data. But if not properly organized, divided, and chosen, even the data that has been gathered is worthless. The lead in this role is data augmentation. Data augmentation aids in organizing the data by assisting with