ApexNeural CV-Net Core

● LIVE TRAINING ACTIVE
Model Architecture & Documentation

Target Recognition Engine (YOLOv8 Modified)

The core vision system utilizes a highly optimized YOLOv8 neural network trained on over 14 million frames of Apex Legends gameplay. It is designed to ignore visual artifacts such as Bangalore's smoke, Gibraltar's dome, and Thermite grenade particle effects. The system calculates character hitboxes in real-time with an average inference delay of just 1.8ms.

Recoil Smoothing & Ballistic Prediction

Recoil compensation is processed through a secondary LSTM (Long Short-Term Memory) network. Currently, the system is actively optimizing the spray patterns for the R-301 Carbine and VK-47 Flatline. It calculates the target's 3D movement vector (X, Y, Z) and applies predictive leading based on the selected weapon's projectile velocity and gravitational drop curves. Sudden acceleration spikes (e.g., Octane's Stim or Horizon's Gravity Lift) trigger heuristic overrides.

Live Training Metrics (Loss Reduction)
GPU_0: RTX 4090 | Temp: 68°C | VRAM: 21.4/24 GB
Node Ping: 12ms
Batch Size: 128
Global Session Stats
Total Frames
0
Confidence
0%
Avg Inference
0ms
Current Loss
0.45
Terminal Output