Verimli Sinir Ağı Mimarileri Araştırması

Sınırlı kaynaklı ortamlar için hafif derin öğrenme modellerinin geliştirilmesi, mobil optimizasyon ve kenar bilişim çözümlerine odaklanarak gerçek dünya uygulamaları sağlar.

Research Breakthroughs

Our latest achievements in neural network efficiency and optimization

85% reduction

Model Compression

Advanced techniques for reducing model size while maintaining accuracy through neural compression and pruning methods.

97.3% accuracy

Performance Optimization

State-of-the-art results on ImageNet and BERT benchmarks with significantly reduced computational overhead.

< 100MB models

Mobile Deployment

Real-world deployment capabilities for mobile and edge devices with optimized inference engines.

Araştırma Alanları

Verimli AI mimarilerindeki ana odak noktalarımız

Neural Network Compression

Advanced methods for reducing neural network size and computational requirements while preserving model accuracy and capabilities.

Post-training and Quantization-Aware Training

Structured and Unstructured Pruning

Knowledge Distillation Frameworks

Low-Rank Factorization Methods

Mobile-First Architectures

Novel neural architectures specifically designed for mobile and edge computing environments with limited resources.

Depthwise Separable Convolutions

Group Convolution Strategies

Neural Architecture Search for Mobile

Hardware-Aware Architecture Design

Edge Computing Solutions

Specialized approaches for deploying AI models on edge devices with real-time performance requirements.

Federated Learning Frameworks

Split Computing Architectures

Inference Engine Optimization

Energy-Efficient Model Design

Verimli AI Araştırmamıza Katılın

Verimli AI mimarilerindeki son bulguları keşfedin ve AI geliştirme süreçlerinizi optimize edin