Projects using TensorFlow in Punjab
Projects using TensorFlow in Punjab
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Yasir Basheer
O-A: Predictive Demand Dashboard
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4
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Shakeel Ur Rehman
Sign Language Detection
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19
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Usman Haider
Trained a DreamBooth LoRA model to generate high-quality, personalized image outputs with consistent subject identity across different prompts and styles. The project involved dataset preparation, image captioning, and fine-tuning diffusion models using LoRA for efficient training and deployment. The solution enables fast generation of customized visuals while preserving subject consistency, style control, and high fidelity, suitable for creative, branding, and content generation use cases.
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98
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Farhan Khan
Real Time SMS Spam Detection/Classification System
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80
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Ayaan Faisal
AI Neural Network for Cats vs. Dogs Classification
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4
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Ihtisham Mehmood
Deep Learning
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5
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Arbab Khan
Earthquake prediction using LSTM
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37
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Arham Malik
Yeah, this one is a bit out there, but it was super fun. I built an AI that actually understands memes. It looks at the image and the text together using PyTorch, TensorFlow, and GPT 4. I used early and late fusion techniques to combine vision and language, plus Tesseract OCR to grab text from the image itself. The model hits over 95% accuracy on meme classification. It’s not your typical corporate project, but it shows how multimodal AI can understand humor, culture, and context. Definitely one of my favorite experiments. For more details, please visit: https://arham-nexus.vercel.app/work/memechecker
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50
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Hammad Bin Sajjad
Pixel Character Sprites Generation
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26
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waqar ahmed
MCTS-UCB Transformer Ensemble
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5
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Fariha Muazzam
At Formulatrix, I led the development of a computer vision pipeline for RockMaker, a biotech product used in crystallization experiments. I built and deployed object detection and image classification models that improved scoring accuracy by 13%, reducing manual effort for scientists and increasing customer satisfaction. The solution was productionized with Docker and CI/CD pipelines, ensuring scalability and reliability across client sites.
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265
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Ali Hamza
Identification of fabric defects using Deep Learning
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12
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Zuha Junaid
Facial Emotion Recognition AI Designed and trained a custom CNN to classify human facial expressions into 7 categories using the FER-2013 dataset. Built an interactive Streamlit dashboard for real-time emotion prediction from images. Implemented class weighting to address dataset imbalance and improved model performance. Custom CNN Architecture Real-time Dashboard 84% Accuracy Technologies Python TensorFlow Keras CNN Streamlit
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Harmain Mughal
Harmain11/Audio_classification
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2
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Abdullah CH
Emotions AI
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7
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Hassan Tahir
Air Pollution Forecasting (Time Series)
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4
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