A machine learning project which can detect and predict the skin disease through image recognition.

Last update: Jan 13, 2022

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Deep Learning ML-Project-2021

Overview

ML-Project-2021

A machine learning project which can detect and predict the skin disease through image recognition. The dataset used for this is the HAM10000 dataset for skin lesions and the project has been done on google colab.

The dataset is imported in and unzipped in the colab for usage, thats why there is a big section where that is shown and and each of the 10000 images and the metadata for the images is uploaded. This is then used in the project. OpevCV had been used for the image recognition part and the major system is based on a CNN model with SVM classification.

Owner

Debshishu Ghosh

A college student.

GitHub Repository

Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

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Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.

This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement

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Multi-Task Learning as a Bargaining Game

Nash-MTL Official implementation of "Multi-Task Learning as a Bargaining Game". Setup environment conda create -n nashmtl python=3.9.7 conda activate

87 Dec 26, 2022

Gif-caption - A straightforward GIF Captioner written in Python

Broksy's GIF Captioner Have you ever wanted to easily caption a GIF without havi

3 Apr 09, 2022

Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction, ICCV-2021".

HF2-VAD Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Predictio

76 Dec 21, 2022

The project is associated with the recently-launched ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge (M2MeT) to provide participants with baseline systems for speech recognition and speaker diarization in conference scenario.

M2MeT challenge baseline -- AliMeeting This project provides the baseline system recipes for the ICASSP 2020 Multi-channel Multi-party Meeting Transcr

81 Dec 08, 2022

A machine learning project which can detect and predict the skin disease through image recognition.

Related tags

Overview

ML-Project-2021

Owner

Debshishu Ghosh

Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression

Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.

Multi-Task Learning as a Bargaining Game

Gif-caption - A straightforward GIF Captioner written in Python

Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction, ICCV-2021".

Official pytorch implementation of paper "Image-to-image Translation via Hierarchical Style Disentanglement".

Compact Bidirectional Transformer for Image Captioning

Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices

ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training

Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"

H&M Fashion Image similarity search with Weaviate and DocArray

Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes

Pytorch implementation of Learning with Opponent-Learning Awareness

PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages

1st place solution in CCF BDCI 2021 ULSEG challenge

A lossless neural compression framework built on top of JAX.

scikit-learn inspired API for CRFsuite

[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Code for the paper "Jukebox: A Generative Model for Music"

The project is associated with the recently-launched ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge (M2MeT) to provide participants with baseline systems for speech recognition and speaker diarization in conference scenario.