L = -1/N ∑ [y_i log(ŷ_i) + (1 - y_i) log(1 - ŷ_i)]Attention(Q, K, V) = softmax(QK^T / √d_k)Vf(x) = 1 / (1 + e^{-x})∇ × E = -∂B/∂tH(p, q) = -∑ p(x) log q(x)E[X] = ∫ x f(x) dxP(A|B) = P(B|A)P(A) / P(B)w^T x + b = 0θ_{t+1} = θ_t - η ∇_θ J(θ)
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Security / Biometrics // 2026-01

Liveness Detection

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Source Code

3D passive liveness detection to prevent print, replay, and 3D mask attacks in identity verification systems. Uses a single RGB camera to estimate depth maps and analyze micro-textures, achieving a BPCER of 0.1% at an APCER of 1%.

Role

AI Researcher

Technologies

TensorFlowMediaPipePython

Use Cases & Advantages

- Financial KYC and Anti-Fraud Systems - Secure Employee Onboarding - Decentralized Identity Proofing - Remote Exam Proctoring Our Stack's Advantage: True passive detection utilizing depth map estimation from just a single RGB stream—no specialized IR cameras required.