An Attention-Enhanced Lightweight CNN Framework with MTCNN Detection and TripletEmbedding Recognition for Occlusion-Robust Automated Attendance from Surveillance Video
An Attention-Enhanced Lightweight CNN framework that couples MTCNN multi-scale face detection with a CBAM (Convolutional Block Attention Module) augmented MobileFace-style backbone trained under triplet loss to produce compact, discriminative 128-dimensional face embeddings from surveillance video is proposed.