In this blog, I will walk through an introduction to instance-level recognition, use cases, challenges, currently available dataset, and state of the art results (recent winner solutions) on these challenges/datasets.
Instance Level Recognition (ILR), is a visual recognition task to recognize a specific instance of an object not just object class.
For example, as shown in the above image, painting is an object class, and “Mona Lisa” by Leonardo Da Vinci is an instance of that painting. Similarly, the Taj Mahal, India is an instance of the object class building.
Images from Google Landmarks Dataset v2 (GLDv2)
#object-detection #machine-learning #deep-learning #data-science #computer-vision
We are witnessing a lot of impacts in the world because of the COVID-19 pandemic. There is not much we could do to compensate for all the losses at once. But it can eventually be overcome. And the reason for this hope is ‘technology’.
Everything is just at an arm’s reach with the technology and it’s been proven time-to-time to us. One such thing that makes people still and stare for a moment is the Face Recognition Employee Attendance Software.
Face recognition is one of the most advanced technologies that is being implemented in the corporate industry now.
The software is mainly responsible for marking the attendance of the employees without them having to touch the screen.
Since ‘touch’ has become the most dangerous word in recent months, the system helps people to get away from it.
This software is also known as Contactless Attendance System that follows a highly hygiene scanning. Let’s look at the workflow:
Working models of the software:
The software works in two different models such as:
The tablet having this software solution, will have to scan their faces at the entry points. They will wait for the system to confirm the checklist like detecting face masks and social distancing.
The mobile-based model is safer, since it involves logging in with the WiFi server and login to the accounts. After matching the criteria, attendance would be marked.
On a concluding note, Employee contactless attendance software is the future. So, make the most out of it by contacting our team right now!
#face recognition attendance software #face recognition employee software #face recognition employee attendance software #face recognition based attendance software #contactless facial recognition attendance system
Python can detect and recognize your face from an image or video
Face Detection and Recognition is one of the areas of computer vision where the research actively happens.
The applications of Face Recognition include Face Unlock, Security and Defense, etc. Doctors and healthcare officials use face recognition to access the medical records and history of patients and better diagnose diseases.
In this python project, we are going to build a machine learning model that recognizes the persons from an image. We use the face_recognition API and OpenCV in our project.
To install the above packages, use the following command.
pip install numpy opencv-python
To install the face_recognition, install the dlib package first.
pip install dlib
Now, install face_recognition module using the below command
pip install face_recognition
#machine learning tutorials #face recognition #face recognition opencv #ml project #python face recognition #face recognition with python
Secure and resizable compute capacity in the cloud.
Amazon Elastic Compute Cloud ( Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.
In this article let us see how to create On-demand EC2 instance from Console.
#create-ec2-instance #aws-ec2-instance #ec2-instance #amazon-web-services #aws
We can extract text data from a speech by using speech recognition methods. There are many ways to carry out speech recognition in Angular, however, I’d like to focus on a simple method for this.
Here we use “Web Speech API” to recognize speech. Unfortunately, this API is only supported for a few browsers so I will list the supported browsers below:
You can test this app in a browser from this list.
Okay, let’s begin. First of all, we have to create a new Angular project by using the below command in the terminal. I assume that you have installed Angular-CLI, but if you haven’t then the below command won’t work.
ng g new voice-recognition cd ./voice-recognition
#speech-recognition #angular #web-speech-api #api #voice-recognition
Explore the features extracted from voice data and the different approaches to building a model based on the features.
#digits-recognition #pytorch #speech-recognition #spoken-digit #convolutional-neural-net