Category: Research Studies
Extractive Summarization of Urdu Language using Deep Learning Techniques on a Custom Dataset
Extractive summarization makes long text easier to understand by picking the most important sentences. Our research focuses on using deep learning to create summaries for Urdu articles. Here’s how we did it: We built a dataset of 1,000 Urdu articles, each representing a unique topic. Using a fine-tuned BERT model, we added extra attention layers […]
Boosting Algorithms in Skin Cancer Diagnosis: Insights from AI Research
Artificial Intelligence (AI) is transforming healthcare by improving diagnostic tools. One significant application is detecting skin cancer. In our recent study, we explored how boosting algorithms can enhance classification accuracy for identifying skin cancer types using the PAD UFES 20 dataset. We started by building a Convolutional Neural Network (CNN) feature extractor to process the […]
NeuralMango: Using AI to Improve Mango Classification and Pricing in Pakistan
Artificial intelligence is transforming agriculture and business, and one example is NeuralMango. This study uses advanced AI techniques to solve a real-world problem in Pakistan’s mango markets. The researchers used EfficientBNet2, a powerful AI model, to classify different types of mangoes and predict their prices. With a dataset of 1,200 mango images, the model achieved an impressive 97% […]
VigilantAI: Real-Time Detection of Anomalous Activity from Video Streams Using Deep Learning
Keeping places secure is a big challenge in today’s world. VigilantAI is a new system that uses Artificial Intelligence (AI) to detect unusual activities like robberies or illegal actions in real-time through video streams. This project started by preparing a dataset of 957 photos of robbery and other illegal activities. These images were labeled using […]