Deep learning projects with source code gives a valuable assistance for both beginners and experienced who looking to learn and explore about new AI Techniques. If you are searching for a best deep learning projects, Then Takeoff Edu Group Provide complete Deep Learning projects with source code, here our experts can bring it to you with complete support and guidance.
Image classification using CNNs is one of the most popular deep learning projects. Since the source code is easily accessible, developers can explore deep into CNN architectures and refine parameters so that they may have a better understanding of image recognition. Likewise, projects that deal with natural language processing have the ability to make users understand what can be achieved by RNNs and transformer models.
Takeoff Edu Group Latest titles of Deep Learning projects with Source Code:
- Face Recognition Door Lock System Using Raspberry Pi
- A Glove that Translates Sign Language into Text and Speech
Face Recognition Door Lock System Using Raspberry Pi
Raspberry Pi is smaller and lighter and it uses less power than a computer or a standard-PC for face recognition. So, project can be implemented with the Raspberry Pi module. Raspberry pi is a secured system once data given, cannot modify that data. It is more secure so used if in this project. This project is not only used for home hold purposes, it’s also used for banks, Hospitals, MNC companies, military purposes and taking attendance for students and faculty in colleges. By using this system, we can decrease the security issues in our daily life because it is the most securable system to get rid of thieves and frauds or other people around our society.
A Glove that Translates Sign Language into Text and Speech
This manuscript presents the research and development of a software that help deaf-mute communication by identifying the position of the fingers of the hand with 5DT gloves. The sign language is adopted by nearly all people with hearing deficiency, making it their main form of communication, but this communication is only successfully achieved if all the participants of the conversation are familiar with the sign language. The goal is to be able to translate hand signs into words and phrases with the possibility to send audio signals to allow deaf-mute users to communicate to people not familiar with the sign language. The recognition of hand gestures is accomplished using a neural network tested using five different training algorithms. A cross-validation experiment is provided to illustrate the robustness of our methods.
These Deep Learning Projects with Source Code contain a wide range of applications, from computer vision and natural language processing to speech recognition and generative models. Takeoff Edu Group furnishes the above titles with an interactive procedure that allows students to gain a better understanding of AI concepts and participate in the ongoing development of artificial intelligence. These projects serve as practical sources of knowledge for aspiring AI enthusiasts who want to build a good foundation in their journey into the world deep learning.