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Deep Learning-Based Vehicle Counting & Classification System
This project develops vehicle counting & classification 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.
Deep Learning-Based Cataract Detection from Eye Images
This project develops cataract detection from eye images 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.
Speaker Identification & Verification using Deep Learning
This project develops speaker identification & verification 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.
Cell Image Classification for Cancer Detection using Deep Learning
This project develops cell image classification for cancer detection 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.
Text Emotion Detection using Transformer-Based Models
This project develops text emotion detection 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.
Deep Learning-Based Forest Fire Detection from Images
This project develops forest fire detection from images 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.
Lip Reading using Deep Learning (Visual Speech Recognition)
This project develops lip reading 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.
Video Summarization using Deep Learning
This project develops video summarization 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 Crowd Anomaly & Violence Detection
This project develops crowd anomaly & violence detection 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.
Real-Time Multi-Face Recognition Attendance System
This project develops real-time multi-face recognition attendance system 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.
Question Answering System using BERT
This project develops question answering system 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 Parking Slot Occupancy Detector
This project develops parking slot occupancy detector 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.