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At first, we extracted only face images from image dataset using MTCNN to remove unnecessary features other than face from the image. Secondly, we used random crop technique for data augmentation to improve the model performance. We have used the concept of transfer learning in our research. A...
face and pedestrian detection using the MTCNN to train - MTCNN-TF/train_models/mtcnn_model.py at master · jimeffry/MTCNN-TF
MTCNN to remove unnecessary features other than face from the image. Secondly, we used random crop technique for data augmentation to improve the model performance. We have used the concept of transfer learning in our research. A pretrained face recognition model i.e VGG-Face is used to build...
A small-scale flask server facial recognition system, using a pre-trained facenet model with real-time web camera face recognition functionality, and a pre-trained Multi-Task Cascading Convolutional Neural Network (MTCNN) for face detection and cropping.
A deep CNN model is used for identification of people's age range in our proposed work. At first, we extracted only face images from image dataset using MTCNN to remove unnecessary features other than face from the image. Secondly, we used random crop technique for data augmentation to ...
An assistive model for visually impaired people using YOLO and MTCNNdoi:10.1145/3309074.3309114Ferdousi RahmanIsrat Jahan RitunNafisa FarhinJia UddinACM PressInternational Conference Cryptography, Security and Privacy
NVIDIA TensorRT implementation for facenet with pre-trained Inception-ResNet v1 SavedModel/Ckpt and MTCNN Networks - JerryJiaGit/facenet_trt