Top 7 Deep Learning Projects for Final Year Students

Deep Learning, which is otherwise regarded as deep neural learning or simply neural learning is the adaption of ML-Machine Learning approach, which was conventionally using networks for learning with the given unlabeled or unorganized data sets. The former ML approaches were able to deploy the straightforward phenomenon, while these evolved deep learning approaches operate with the help of Neural Network (NN) with the primary aim to replicate the thinking as well as the learning capabilities of human beings. In piece of write-up, we have curated the Top 7 Deep Learning Projects for Final Year Students and discussed those 7 project ideas in the below sections.

Here are the Top 7 Deep Learning Projects for Final Year Students for learning and skillset development purposes:

1. A Deep Learning Facial Expression Recognition-Based Scoring System for Restaurants

There are many novel ways of rating the restaurants from the conventional practice like user google rating to the automated practice like the co-corporate (Zomato, Swiggy) ratings being made for the restaurants based on several taken parameters.

In this research instance, a novel methodology of deep learning could be used to in order to identify several kinds of facial expressions of human beings to develop a robust scoring approach and review both the surrounding of the restaurants and taste of the food items available there. 

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like NN- Neural network, sensory devices, cloud computing, data analytics, image processing, Hotel-related features, face emotions/ attributes, and several other advanced software tools for completing their projects successfully.

2. A Cascade Broad Neural Network for Concrete Structural Crack Damage Automated Classification 

As the structures of buildings/ establishments are becoming more and more sophisticated because of diverse needs of human kind, it becomes almost impossible to test and eliminate the cracks/ damages in those sophisticated structures (for instance, concrete material).

By making use of the cascaded NN, it is possible to develop a robust testing approach which is able to identify every possible crack/ damage found in the considered concrete structures used in several recent age buildings.

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like NN, Knowledge of construction, metallurgy, sensory devices, cloud computing, data analytics, and several other advanced software tools for completing their projects successfully.

Must Read: Deep Learning Project Ideas & Titles

3. Ophthalmic Disease Detection Using Deep Learning 

With the number of people getting blind is increasing due to several other heath complications, it is necessary to identify the risks related to every ophthalmic ailment to prevent blindness. 

By integrating deep learning concepts and an innovative mixture loss function, it is possible to automate the operation of detection of several ophthalmic ailments in human beings by carefully investigating the retinal fundus pics.

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like sensory devices, cloud computing, data analytics, image process, medical care systems, and several other advanced software tools for completing their projects successfully.

Read: List of Machine Learning Project Ideas

4. Vitamin Deficiency Detection Using Image Processing and Neural Network

We often tend to neglect the indications/ symptoms that we develop in our body, which could later on contribute to develop a serious health impairment. 

With the deployment of CNN- Convolutional Neural Network, incorporations of Open CV and adopting proper pre-processing, it is possible to develop a vitamin deficiency identifying technique by careful assessment of several bodily organs of human beings. 

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like CNN, sensory devices, cloud computing, data analytics, image process, medical care systems, and several other advanced software tools for completing their projects successfully.

Also Try: IEEE Projects on Embedded Systems

5. A Novel Time-Aware Food Recommender-System Based on Deep Learning and Graph Clustering

The development of recommender systems has become prevalent in many sectors, which doesn’t leave out the food sector.

With the deployment of deep learning concepts and incorporating applicable clustering, an innovative and efficient food recommending system could be developed by making the system to learn a set of pre-defined food items and data of the users. 

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like clustering, food attributes, user preference attributes, sensory devices, cloud computing, data analytics, and several other advanced software tools for completing their projects successfully.

6. Real Time Object Detection with Audio Feedback using Yolov3 

Practical object detection is quite common for any co-operate companies to adopt for building robots, self-driving cars, etc. However, not all blind persons make use of these practically viable object detection methodologies in their daily routines. 

 A more practically viable object detection system could be developed by making use of Yolov3 (You Only Look Once, Version 3) along with the feedback provided with the help of the speaker. This could be put into practice for fulfilling the blind person’s daily routines so that it could be more effective.

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like basics of YOLOv3, sensory devices, cloud computing, data analytics, image processing, speaker, and several other advanced software tools for completing their projects successfully.

7. Ischemic and hemorrhage stroke prediction using DL algorithm 

Incorporation of deep learning methodology will be very indispensable in the sector of health care. Especially, in detecting the risks of stroke conditions in human beings.

With the incorporation of methodology of deep learning, even the critical stroke conditions like hemorrhage and Ischemic strokes could be easily diagnosable by the specialized physicians. 

While doing any kind of deep learning projects serving numerous applications, one should realize about the following elements/ concepts like sensory devices, cloud computing, data analytics, image processing, medical care systems, and several other advanced software tools for completing their projects successfully.

Know more: Ischemic and hemorrhage stroke prediction using DL algorithm