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12
Mar
Face Recognition with MTCNN and FaceNet; RL with Proximal Policy Optimization

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #AlwaysUpskilling Minutes from Saturday 7th March 2020 AI Lab meetup at BLR :- Last Saturday, we had excellent sessions in the AI Lab meetup. Face Recognition with MTCNN and FaceNet :- First Amit Kumar presented a detailed overview of Face Recognition with MTCNN and FaceNet. Face Recognition involves a pipeline of Face […]

Posted in: Computer Vision, Deep Learning, Reinforcement Learning, Security,
Tags: Advantage Function, Face Recognition, facenet, Important Sampling, MTCNN, MTCNN face detector, O-Net, PG algo, policy based methods, policy gradients, PPO, proximal policy optimization, R-Net, reinforcement learning, Triplet Loss, Value-based methods, Vanilla Policy Gradient, VPG,
04
Dec
1
Face Recognition with MTCNN and FaceNet

#CellStratAILab #disrupt4.0 #WeCreateAISupertars Last Saturday, CellStrat AI Lab Team Lead Niraj Kale presented an intuitive hands-on workshop on Face Recognition with MTCNN and FaceNet algorithms. The session included a theory presentation along with an extensive hands-on code workshop. This model has two networks at play. First, the MTCNN localizes the face by creating a bounding […]

Posted in: Auto and Manufacturing, Computer Vision, Deep Learning, Security,
Tags: AI lab, CNN, Computer Vision, deep learning, Disrupt4.0, face detection, Face Embeddings, Face Recognition, facenet, MTCNN, Multi-task Loss, object detection, object localization, Triplet Loss,
03
Dec
Facial Recignition System in Dept. of Homeland Security
Posted in: Artificial Intelligence, Computer Vision, Deep Learning, Industry, Security,
Tags: AI, CNN, DL, government, images, ML, Security,
31
Oct
Meeting Minutes from AI Lab session on Saturday 26th Oct in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Last Saturday we had another fantastic set of AI presentations at our AI Lab meetup. Face Recognition System with MTCNN :- First, Jani Basha presented a fabulous model on face recognition system, which involved detecting and recognizing faces from images and videos. One can also use this model to identify humans from […]

Posted in: Computer Vision, Cyber Security, Deep Learning, Generative Modeling, Machine Learning, Security,
Tags: AI, AI lab, artificial intelligence, Computer Vision, deep learning, Deepfake, Disrupt4.0, DL, Face Recognition, Face2face, Fake Video Detection, forged videos, machine learning, Mesoscopic, ML, monte carlo, MTCNN, MTCNN face detector, roulette, stock price prediction, video analytics,