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abdur75648 / Deep-Learning-Specialization-Coursera

Star 373

This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc.

nlp machine-learning computer-vision deep-learning tensorflow coursera recurrent-neural-networks lstm neural-networks face-recognition convolutional-neural-networks object-detection andrew-ng updated deep-learning-specialization deep-learning-coursera andrew-ng-machine-learning deep-learning-andrew-ng transformer-architecture unet-segmentation
  • Updated Feb 9, 2024
  • Jupyter Notebook

cuiziteng / Illumination-Adaptive-Transformer

Star 433

[BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.

image-reconstruction pytorch image-restoration image-enhancement low-level-vision transformer-architecture exposure-correction bmvc low-light-enhance transformer-models low-light-image-enhancement
  • Updated Feb 27, 2024
  • Python

zhongkaifu / Seq2SeqSharp

Star 190

Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on.

image translation deep-learning neural-network gpu text machine-translation cuda transformer lstm seq2seq sequence-to-sequence tensor encoder-decoder attention-model transformer-encoder transformer-architecture vision-transformer
  • Updated May 16, 2024
  • C#

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