current research topics in deep learning


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Some of the concepts of deep learning that have gained attention and suggested below. All the details related to your work with up-to-date ideas will be shared for our scholars. Here we explain about deep learning theories, like design, architecture, workflow and algorithms. We carry on research work and attain a value-added application to the selected areas.

  1. Capsule Networks:
  • Through the utilization of Capsule networks rather than using conventional neural network, we can understand the spatial hierarchical relationships among various features.
  1. Transformers beyond NLP:
  • We developed transformers for NLP based procedures and it provides an efficient performance in various platforms like computer vision, protein folding and others.
  1. Methods for augmenting data:
  • To build an effective framework, we utilized innovative ideas for data augmentation like CutMix, MixUp, etc., particularly in vision domain.
  1. Explainable AI (XAI):
  • We properly developed our DL techniques for making understandable decisions because, initially, DL approaches are considered as black boxes.
  1. Self-supervised learning:
  • To minimize the requirement for manually labeled data, we employed self supervised learning technique to train the framework by utilizing obtained labeled data from the input data.
  1. Neural Radiance Fields (NeRF):
  • NeRF offers an effective outcome for high fidelity 3D redevelopment. So, we also used it for 3D scene visualization and rendering.
  1. Federated learning:
  • For secure and reliable AI model, we train our model on distributed data through the deployment of federated learning techniques.
  1. Pros and cons in AI:
  • We need to check whether the AI framework is robust and efficient by solving the problems like disadvantages of framework and discriminatory decisions.
  1. Neural Architecture Search (NAS):
  • To find out the best network architectures, we apply automated techniques.
  1. Integrated frameworks:
  • We ensembled DL method with other conventional techniques or integrated various kinds of neural networks to enhance the model’s efficiency.
  1. Out of Distribution (OOD) identification:
  • To identifying and managing inputs that are contrasted from the data utilized we train the framework.
  1. Multimodal and Cross modal learning:
  • To train and represent the data more precisely, we combined several types of data such as text pattern, image and audio patterns.
  1. Temporal and lifelong learning:
  • By this, our model can adapt and learn in an actual time without forgetting the skills that are learned before.
  1. Knowledge Distillation:
  • From the utilization of knowledge distillation more effectively, we trained our small model (i.e student) to obtain the characteristics of complicate and huge model (i.e staffs).
  1. Quantum Neural Networks:
  • The common facts of quantum computing and neural network approaches will be analyzed.
  1. Techniques for effective training:
  • By analyzing several energy efficient training techniques, we can minimize the environmental effect of DL.

To know about the current researches related to AI, we analyse the investigations of popular AI conferences like NeurIPS, ICML, ICLR, CVPR, or ACL for the current year and we research about other evolving concepts in various particular conferences.


All types of MPhil dissertation topics on deep learning will be guided by us. Trending topics and its work structure will be briefly explained. We stay updated on current topics to satisfy our customer needs. If you are looking for genuine research guidance for your doctoral research on deep learning matlabsimulation.com serves as a best idea. Some of the latest topics has been discussed below, while we tailored out your own topics.

  1. Deep Learning-Based Receiver Energy Prediction in Energy Harvesting Wireless Sensor Network
  2. An Autonomic Deep Learning Artificial Neural Network based Algorithm for Effective Re-generation
  3. A novel deep learning method for application identification in wireless network
  4. A New Deep Learning Method for Multi-label Facial Expression Recognition based on Local Constraint Features
  5. A multi-view deep learning approach for predictive business processes monitoring
  6. An Improved Kubernetes Scheduling Algorithm for Deep Learning Platform
  7. Deep Learning-based Action Recognition for Pedestrian Indoor Localization using Smartphone Inertial Sensors
  8. Towards 6G Networks: Ensemble Deep Learning Empowered VNF Deployment for IoT Services
  9. A New Deep Learning Method for Underwater Target Recognition Based on One-Dimensional Time-Domain Signals
  10. Bitcoin Price Prediction: A Deep Learning Approach
  11. Performance Comparison of Fuzzy Logic and Deep Learning algorithms for fault detection in electrical power transmission system
  12. Prediction of Mortality and Length of Stay with Deep Learning
  13. A Deep Learning Module Design for Workspace Identification in Manufacturing Industry
  14. Incident Detection based on Multimodal data from Social Media using Deep Learning Methods
  15. Exploiting 2D Coordinates as Bayesian Priors for Deep Learning Defect Classification of SEM Images
  16. Using Deep Learning Network for Fault Detection in UAV
  17. Simulation of Temperature Distribution During HIFU Therapy Using Physics Based Deep Learning Method
  18. Experimental Design for Multi-task Deep Learning toward Intelligence Augmented Visual AI
  19. Comparison of Semantic Segmentation Deep Learning Methods for Building Extraction
  20. Application of Advanced Deep Learning Techniques for Face Detection and Age Estimation
  21. All You Need is Transformer: RTT Prediction for TCP based on Deep Learning Approach
  22. Salient Region Detection in Images Based on U-Net and Deep Learning
  23. Modelling of Wireless OFDM System with Deep Learning-based Modulation Detection
  24. Xonar: Profiling-based Job Orderer for Distributed Deep Learning
  25. A Deep Learning Method for Pneumonia Detection Based on Fuzzy Non-Maximum Suppression
  26. Optimization of Deep Learning based Tone Reservation
  27. Intelligent Repair Method of Old Movie Speckle Noise Based on AI Deep Learning
  28. A Deep Learning Approach for Stress Detection Through Speech with Audio Feature Analysis
  29. A Hybrid Deep Learning Spectrum Sensing Architecture for IoT Technologies Classification
  30. GSP Distributed Deep Learning Used for the Monitoring System
  31. Regional Heatwave Prediction Using deep learning based Recurrent Neural Network
  32. Recommendation-based Security Model for Ubiquitous system using Deep learning Technique
  33. Point-Cloud-based Deep Learning Models for Finite Element Analysis
  34. Employing Deep Learning and Discrete Wavelet Transform Approach to Classify Motor Imagery Based Brain Computer Interface System
  35. Prediction of regional ecological security by applying deep learning methods in spatial and temporal simulation
  36. Webshell Detection Technology Based on Deep Learning
  37. Concept Drift Detection Methods for Deep Learning Cognitive Radios: A Hardware Perspective
  38. Deep Learning Based Multi Modal Approach for Pathological Sounds Classification
  39. Design of Deep Learning Algorithm in the Control System of Intelligent Inspection Robot of Substation
  40. 3D Reconstruction of Forearm Veins Using NIR-Based Stereovision and Deep Learning
  41. CT Dataset Enhancement using Additional Feature Insertion for Automatic Femur Segmentation Model Based on Deep Learning
  42. A Comparative Study of Machine Learning and Deep Learning Techniques for Sentiment Analysis
  43. Over The Air Performance of Deep Learning for Modulation Classification across Channel Conditions
  44. Accurate Precipitation Prediction using Deep Learning Neural Network Compared with Space Vector Machine
  45. Interpreting Deep Learning Models for Multi-modal Neuroimaging
  46. Bitcoin Price Prediction Using Deep Learning and Real Time Deployment
  47. Research on green building optimization design of smart city based on deep learning
  48. Introduction to Deep Learning Possibilities in Communication Systems
  49. An Enhanced Method on Using Deep Learning Techniques in Supply Chain Management
  50. Impact Analysis of Incident Angle Factor on High-Resolution Sar Image Ship Classification Based on Deep Learning

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