الصفحة 1
الصفحة 1
Elevating video content creation with ai assistance = ارتقاء إنشاء محتوى الفيديو بمساعدة الذكاء الاصطناعي
We developed an AI Assistant equipped with features such as description crafting, title generation, keyword extraction, image captioning, clickbait detection, and sentiment analysis.To achieve these functionalities, we proposed a model for generating video descriptions using ResNet50 as a feature extractor and a LSTM network with an attention mechanism as a sequence generator, achieving a BLEU-1 score of 0.907 and a ROUGE-L score of 0.645. For keyword extraction, we utilized Sentence Transformer to identify strategically relevant keywords from the generated descriptions. For title generation, we fine-tuned the BART model, achieving a ROUGE-L score of 0.45. For clickbait detection, we used SVC classifier with linear kernel and TF-IDF vectorization for feature extraction, resulting in 96% accuracy. Our sentiment analysis model using a CNN-LSTM architecture achieved 80% accuracy in analyzing comments on videos. For image captioning, we employed a feature extractor with a CNN layer followed by an LSTM model, achieving a BLEU-1 score of 0.53. Our platform empowers creators by simplifying complex tasks and offering deeper audience engagement insights, making it a powerful tool in the evolving digital content creation.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
A. H Medical Center
مشروع المركز الطبي هو عبارة عن منظومة متكاملة يتواجد فيها كافة التخصصات الطبية والمخبرية في مكان واحد. تم اختيار موقع المشروع في ماروتا سيتي نظراً إلى اعتماد النمط المعماري الحديث ضمن المنطقة مما يتناسب مع النمط الذي تم اعتماده في التصميم للمشروع. ويتضمن المشروع قسم العيادات بمجموع ٣٠ عيادة بكافة التخصصات مع قسم خاص للتصوير الاشعاعي بكافة تخصصاته، قسم عناية مركزة، قسم إسعاف، مخبر، غسيل كلى، صيدلية وكافة الخدمات اللازم تواجدها فيمثل هذه المشاريع.
