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Text-to-Image Generation using GAN/Diffusion Models
This project develops text-to-image generation using a ResNet/EfficientNet backbone trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Deep Learning-Based Named Entity Recognition System
This project develops named entity recognition system using a GAN-based generative architecture trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Speech-to-Text Transcription using Deep Learning
This project develops speech-to-text transcription using a CNN-LSTM hybrid architecture trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Deep Learning-Based Retinal Disease Detection from Eye Scans
This project develops retinal disease detection from eye scans using a GAN-based generative architecture trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Deep Learning-Based Deepfake Image Detector
This project develops deepfake image detector using a 3D-CNN for spatio-temporal data trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Autonomous Lane Detection using Deep Learning
This project develops lane detection using a Transformer-based model (BERT/ViT) trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Deep Learning-Based Currency Note Fraud Detection
This project develops currency note fraud detection using a GAN-based generative architecture trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Deep Learning-Based Facial Emotion Recognition System
This project develops facial emotion recognition system using a YOLO-based real-time detector trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Employee Productivity Prediction using ML
This project builds a data-driven pipeline for employee productivity prediction using ensemble stacking of multiple classifiers trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Delivery Time Prediction for Logistics using ML
This project builds a data-driven pipeline for delivery time prediction for logistics using Logistic Regression and SVM trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Deep Learning-Based Face Mask Detection System
This project develops face mask detection system using a YOLO-based real-time detector trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Crop Recommendation System based on Soil Data using ML
This project builds a data-driven pipeline for crop recommendation system based on soil data using K-Means and hierarchical clustering trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.