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Deep Learning-Based Brain Tumor Segmentation from MRI
This project develops brain tumor segmentation from mri using an LSTM/GRU sequence model 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.
Image Colorization using Deep Convolutional Networks
This project develops image colorization using a Convolutional Neural Network (CNN) 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 Anomaly Detection in Surveillance Video
This project develops anomaly detection in surveillance video 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.
Deep Learning-Based Skin Cancer Classification System
This project develops skin cancer classification system using an LSTM/GRU sequence model 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.
Deep Learning-Based Age & Gender Detection from Face
This project develops age & gender detection from face 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.
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.
Music Generation using LSTM/RNN Networks
This project develops music generation 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 Traffic Sign Recognition System
This project develops traffic sign recognition system using an LSTM/GRU sequence model 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.