Image Processing, NLP, and Neural Networks

ما هو الهدف الرئيسي من معالجة الصور الرقمية؟

ما هو 하나 من التطبيقات الرئيسية لمعالجة الصور الرقمية؟

ما هو الاسم الذي يطلق على دالة التفعيل في الشبكة العصبية التي تربط بين ميزات دالة.SIGMOID و دالة.RELU؟

ما هو أحد المزايا الرئيسية لدالة LLMS؟

ما هو أحد التطبيقات الهامة لدالة LLMS؟

ما هو يعرف بمجال 교집합 بين علم الكمبيوتر والذكاء الاصطناعي واللغويات؟

ما هو هدف معالجة اللغة الطبيعية؟

ما هو أحد التطبيقات الحديثة لمعالجة اللغة الطبيعية؟

ما هو هدف معالجة الصور الرقمية في السيارات ذاتية القيادة؟

Image Processing

Definition: Altering or manipulating digital images using mathematical algorithms to enhance, analyze, or extract information.
Applications:
- Image recognition and classification
- Object detection and tracking
- Image segmentation and feature extraction
- Image restoration and enhancement
Techniques:
- Filtering (e.g., convolutional filters)
- Thresholding
- Edge detection
- Morphological operations
AI and ML applications:
- Facial recognition
- Object detection in self-driving cars
- Medical image analysis

LLMS (Limited Memory Limited Slope)

Definition: A type of neural network activation function that combines the benefits of the sigmoid and ReLU functions.
Characteristics:
- Similar to sigmoid for negative inputs
- Similar to ReLU for positive inputs
- Has a limited range of outputs
Advantages:
- Fast computation
- Easy to compute derivatives
- Can be used with stochastic gradient descent
Applications:
- Natural Language Processing (NLP)
- Computer Vision

NLP (Natural Language Processing)

Definition: The intersection of computer science, artificial intelligence, and linguistics focused on human-computer interaction.
Goals:
- Language understanding
- Language generation
- Sentiment analysis
- Text classification
Techniques:
- Tokenization
- Named Entity Recognition (NER)
- Part-of-Speech (POS) tagging
- Dependency parsing
Applications:
- Chatbots and virtual assistants
- Sentiment analysis for customer feedback
- Language translation
- Text summarization

Test your knowledge of image processing techniques, neural network activation functions, and natural language processing concepts. Covers applications in AI, ML, and computer vision.