Disrupt4.0

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Sep

#CellStratAILab #disrupt4.0 #AIforKids #disruptforkids #WhereLearningNeverStops Image Credit : https://bit.ly/2RUv59W; https://bit.ly/2RRXQ6O CellStrat AI Lab is pleased to present CS SmartKids Program – AI ML Training for Kids. Dear Parents, Are you looking for AI ML Training for your emerging Tech Star kids ? Is your child interested in learning new technologies with real-world […]

Posted in: Deep Learning, Machine Learning, SmartKids,

Tags: AI courses for kids, AI for Kids, AI kids, Coding for children, Coding for kids, CS SmartKids, Disrupt for Kids, Disrupt4.0, kids AI lab, Kids Coding Class, Kids ML course, Kids Python Class, ML course for kids, programming classes for kids, python course for kids, python for kids, SmartKids, SmartKids Lab,

Jul

CellStrat AI Platform for Healthcare Applications

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Recently, we conducted our first Product Showcase for our new world-class Healthcare AI application platform. Given the times, COVID-19 detection is our top focus in terms of product development, but we also have other exciting healthcare AI applications being developed related to brain, eye and cancer issues. The following demos were presented […]

Posted in: Brain and Neurology, Computer Vision, COVID-19, Deep Learning, Eye and Vision,

Tags: 3D CNN, AI lab, AI product, AI research, AWS, brain lesion, Brain Lesions, Chest X-Ray, Conditional Random Fields, COVID-19, CRF, CT Scan, data augmentation, DeepMedic, diabetic retinopathy, Disrupt4.0, explainable AI, eye disease, Grad-CAM, healthcare AI, image classification, image segmentation, INFNET, Magnetic Resonance Imaging, MRI, pneumonia, sagemaker, TBI, Traumatic Brain Injury, UNET,

Dec

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,

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,

Oct

Meeting Minutes from AI Lab Hands-On Workshop on Saturday 19th Oct in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Last Saturday, our AI Lab Team Leads Abdul Azeez and Indrajit Singh conducted a superb workshop on developing Question-Answer systems (QAS) with Natural Language Processing or NLP. The Question and Answering systems are going to change the world. Understanding human language interactively, accurately and faster is the need of the century. There […]

Posted in: Deep Learning, Natural Language Processing,

Tags: AI lab, artificial intelligence, deep learning, Disrupt4.0, disruption, EM score, encoder-decoder, exact-match, GLoVe, GLoVe embeddings, Long Short-term memory models, LSTMs, natural language processing, NLP, QAS, Question-Answer Model, RNNs, Sequence-to-sequence, SQuaD, Stanford Question Answering Dataset, Stanford SQuaD,

Sep

Meeting Minutes from AI Lab session on Saturday 31st Aug in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Last Saturday, we had AI Lab meetups at Bengaluru (Bellandur and Hebbal locations). Deep AI sessions were presented in both locations. In Bellandur, we saw a great session on Singular Value Decomposition (SVD) by Sai Sundarakrishna. SVD is a matrix factorization technique to discover the constituents of a matrix. As opposed to […]

Posted in: Computer Vision, Deep Learning, Machine Learning,

Tags: 3D brain tumor detection, 3D CNN, AILab, artificial intelligence, Baidu DeepSpeech, Bi-Directional RNNs, BiRNN, Computer Vision, data analytics, data science, deep learning, Deep RNN, DeepSpeech, Disrupt4.0, GRU, image segmentation, LSTM, machine learning, matrix factorization, Recurrent Neural Networks, RNNs, seasonality, Singular Value Decomposition, stationarity, SVD, Time-series, trend, trends, UNET,

Aug

Meeting Minutes from AI Lab session on Saturday 3rd Aug in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars CellStrat AI Lab is setting the standard for AI innovation in India ! We are India’s No 1 AI Lab ! Next stop – global AI disruption. The AI Lab meetup on 3rd Aug in Bengaluru saw deep presentations on cutting-edge AI. The day started with a superb presentation by Monisha H. […]

Posted in: Computer Vision, Deep Learning, Driverless Cars, Natural Language Processing,

Tags: 3D CNN, Computer Vision, Disrupt4.0, driverless cars, Faster RCNN, natural language processing, NLP, object detection, Ranked Retrieval, Region Proposal Network, RPN, video analytics,

Aug

Meeting Minutes from AI Lab session on Saturday 27th July in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars CellStrat AI Lab had intense Lab meetups last Saturday in Bengaluru at our Bellandur and Hebbal locations. CellStrat AI Researcher Abdul Azeez spoke on Object Detection using a variety of techniques, starting with a traditional method called Viola/Jones Face Detector. This is a popular method for real time object detection (e.g. used […]

Posted in: Computer Vision, Deep Learning, Natural Language Processing,

Tags: Batch normalization, Disrupt4.0, Gaussian Mixture, ImageNet, Inception Network, inception v1, inception v2, Inception V3, integral image, LibriTTS, mAP, natural language processing, NLP, RMSProp, Speech to Text, Text to Speech, WaveRNN,

Jul

Meeting Minutes from AI Lab session on Saturday 20th July in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars CellStrat AI Lab had remarkable presentations last Saturday in the AI Lab meetup. First Vivek Singhal (Co-Founder & Chief Data Scientist, CellStrat) started with a deep-dive into Convolutional Neural Networks or CNNs, specialized neural networks which are useful for image processing applications particularly. CNNs work by applying a kernel filter weight matrix […]

Posted in: Deep Learning, Machine Learning,

Tags: AI lab, artificial intelligence, AutoKeras, automl, AutoWEKA, Bayesian optimization, CNN, Decision Trees, deep learning, Disrupt4.0, generative modelling, grid search, H2O.ai, image processing, image segmentation, KNNs, machine learning, object detection, parameter search, pose extraction, random search, sequential models, TPOT,

Jul

Meeting Minutes from AI Lab session on Saturday 13th July in Bengaluru

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars CellStrat AI Lab is making waves every week with new project presentations and research discussions in advanced AI and Machine Learning. In the AI Lab last Saturday, the first session saw Indrajit Singh presenting a deep dive seminar on the topic “Information Retrieval from Textual Data“. In Natural Language Processing, one of […]

Posted in: Computer Vision, Deep Learning, Natural Language Processing,

Tags: AI lab, artificial intelligence, CNNs, deep learning, Disrupt4.0, googlenet, Inception Networks, inception v1, inception v2, machine learning, NER, Next sentence prediction, research, SQuaD, text mining, Word2Vec,