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DEJAVU HD (1)
⏲ 2 min 23 sec ✓ 08-Jul-2023
T: The New York Times Style Magazine - THE SCENEMAKERS, 2020
⏲ 60 sec ✓ 28-Aug-2020
The 'images' that 10 neurons in a simple neural network use to predict the probability of a digit.
⏲ 21 sec ✓ 10-May-2021
Deep Learning for Robotic Mass Transport Cloaking
⏲ 13 sec ✓ 03-Oct-2019
TIGHTER SKIRT
⏲ 1 min 67 sec ✓ 21-Oct-2021
I11-ML Chessboard App
⏲ 1 min 43 sec ✓ 30-Apr-2021
Opposite shoes WEB 30s
⏲ 30 sec ✓ 24-Nov-2023
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⏲ 76 sec ✓ 01-Feb-2022
Reverse image Search Engine in Python
⏲ 84 sec ✓ 04-Sep-2022
TIGHTER SKIRT BEHIND THE SCENE
⏲ 7 min 32 sec ✓ 04-Dec-2021
Desencanto
⏲ 56 sec ✓ 19-May-2022
4. 1St Model Nn
⏲ 2 min 88 sec ✓ 15-Apr-2023
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_dejavu-hd-1.webp "D E J A V Un@malviemagnnCREATIVE DIRECTION/FASHION STYLINGn@angela.lezamaen@paola_gmgn@tatitafurnnPHOTOGRAPHYn@marcguerrerophotonnMUAn@saralouzao.mkpnnMODELn@_baara.g.e._n@twomanagementbarcelonannSPECIAL THANKSn@nn_pressn@marialuisadeespanan@marcjuancomunicacionn@fernandorodriguezdesign_")
_t-the-new-york-times-style-magazine-the-scenemakers-2020.webp "A short film I directed for T: The New York Times Style Magazine.nFeaturing: the writer and model SEASHELL COKER; the designer VICTOR BARRAGÁN; the model and Dick Appointment host HALLE CHERRY, the designer AYLA ARGENTINA; the D.J. and Papi Juice co-founder OSCAR NÑ; the designer CARLY MARK; the designer RAFFAELLA HANLEY; the artist, D.J. and Club Glam co-founder DESE ESCOBAR, the makeup artist and Bubble_T co-founder STEVIE HUYNH; the D.J. and GHE20G0TH1K founder VENUS X; the photographer and")
_the-39images39-that-10-neurons-in-a-simple-neural-network-use-to-predict-the-probability-of-a-digit.webp "The network has just one linear layer (nn.Linear(64,10) layer))! It is training on the Scikit-Learn Digits dataset. Each frame shows what the 'image' per neuron looks lik after one epoch of training the model.")
_deep-learning-for-robotic-mass-transport-cloaking.webp "Authors: Reza Khodayi-mehr and Michael M. ZavlanosnnDescription: The contour plot on the left shows the NN approximation of the time-dependent AD-PDE obtained after solving the Mass Transport Cloaking (MTC) problem. The contour plot in the middle shows the FE solution obtained for the final optimal controls whereas the contour plot on the right shows the error between the NN and FE solutions. Note that although the NN solution is learned while solving the MTC problem where the PDE constraint is")
_tighter-skirt.webp "If you were to say to me that I couldn't paint, I would write. If I couldn't write, I would be a set designer. As long as I'm creating something, I'm happy. Do what's make you happy take idea and employ yourself no one will bring you a job your hard work....nnSong: #tighterskirt nProducer: @riccobeatznArtist: @makmansa nDirector: @ondivow_photography nProduction design/Set Design: @mr_.elijah @_.a.s.e.e._nModel: @l.y.nn.enBTS: @aboi_falcon_photography nGrips/lighting: nn#tighterskirt #music #set")
_i11-ml-chessboard-app.webp "The ML Chessboard Application is a showcase of how we can use Machine Learning in low power systems like an MCU. The application uses a Machine Learning model to identify the state of a chessboard by analyzing every piece on the board individually. The machine learning model uses the CMSIS-NN framework and is trained on the MNIST number recognition dataset. The system also requires image processing and embedded systems knowledge for the Arducam MT9D111 camera module. This project is simply a sho")
_opposite-shoes-web-30s.webp "Director: Nemanja Novaković nDOP: Lazar Bogdanović nProducer: Aleksandar Pejčić nProduction: NN media nColor: Nikola Marinković nEditor: Marko DžambićnClient: Opposite FashionnnModel : Famous Serbian singer Nataša Bekvalac")
_92.webp "Shop the collection now on www.bymoumi.com/shopnnModel: @liaantonova nPhotographer: @superverysnapshot nAssistant: @sometime_seed nStylists: @nn.nani @choltida nMUA: @31monthly nnMusic: “Spinning For the Cause” by I got you on tape.")
_reverse-image-search-engine-in-python.webp "Problem statement:nA reverse image search engine based on the fundamental Deep Learning algorithm, viz., K-NN algorithm(K-Nearest Neighbours). nnnExploratory Data Analysis (EDA) and Data preparation:nAs for data collection, we used a publicly available dataset sourced from kaggle which contains ~4700 images to train our model and used the scikit.learn library to extract and process features out of the query(the image uploaded by the user) image.nnnModel Training and Evaluation:nPost data collect")
_tighter-skirt-behind-the-scene.webp "Song: #tighterskirt nProducer: @riccobeatznArtist: @makmansa nDirector: @ondivow_photography nProduction design/Set Design: @mr_.elijah @_.a.s.e.e._nModel: @l.y.nn.enBTS: @aboi_falcon_photography nGrips/lighting:")
_desencanto.webp "Desencanto for @moevir.parisnnnTEAMnStylist @y.ibanez_nArt director @theprayingmanntisnMUA @ainara.muanRigger @canittnPRODUCCIÓNn@santolente.studionPhoto @henryf.photographernOP @ricardomadrid_nBTS @aitordiagonMODELSn@kamaittachin@imjess_ccnAGENCYn@mira_model_managementnn@nn_pressn@blendbcnshowroomn@arsetten@marcjuancomunicacionn@mira_model_management")
_4-1st-model-nn.webp "4. 1St Model Nn from nn model")
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