brianlcm

brianlcm's Stars

• erdpx/vesuvius-grand-prize

  Vesuvius Challenge: code for the second-place winner of the Grand Prize

  Language:Python272

• Project-Platypus/Platypus

  A Free and Open Source Python Library for Multiobjective Optimization

  Language:Python565153

• scikit-optimize/scikit-optimize

  Sequential model-based optimization with a `scipy.optimize` interface

  Language:Python2.7k547

• aideep1400/Cattely-Cattle-Face-Images-Dataset

  A sample of front profile images of 50 cattle, with 50 images per cattle, facilitating research in cattle facial recognition, breed classification, and machine learning algorithms for cattle facial feature analysis

  61

• alexgoft/BERT-Binary-Classifier

  A text classifier utilizing BERT models in Python. The classifier can be fine-tuned for a variety of text classification tasks, such as sentiment analysis, spam detection, and topic classification.

  Language:Python3

• arthurdouillard/incremental_learning.pytorch

  A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).

  Language:Python38460

• Paulo-Rozatto/subvisor

  Polygon annotation tool

  Language:JavaScript1

• WongKinYiu/yolov9

  Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

  Language:Python8.9k1.4k

• anyoptimization/pymoo

  NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

  Language:Python2.2k382

• scabini/RADAM

  We propose a new method named Random encoding of Aggregated Deep Activation Maps (RADAM) for feature extraction from pre-trained Deep CNNs. The technique consists of encoding the output at different depths of the CNN using a Randomized Autoencoder, producing a single image descriptor

  Language:Python321

• G-U-N/a-PyTorch-Tutorial-to-Class-Incremental-Learning

  a PyTorch Tutorial to Class-Incremental Learning | a Distributed Training Template of CIL with core code less than 100 lines.

  Language:Python828

• G-U-N/PyCIL

  PyCIL: A Python Toolbox for Class-Incremental Learning

  Language:Python784136

• Rhyssiyan/DER-ClassIL.pytorch

  The official PyTorch code for 'DER: Dynamically Expandable Representation for Class Incremental Learning' accepted by CVPR2021

  Language:Python15320

• YellowPancake/TCIL

  Official Pytorch implementations of TCIL, accepted at AAAI 2023

  Language:Python161

• limberc/deeplearning.ai

  Language:HTML19796

• scikit-learn/scikit-learn

  scikit-learn: machine learning in Python

  Language:Python59.6k25.3k

• rodrigo-arenas/Sklearn-genetic-opt

  ML hyperparameters tuning and features selection, using evolutionary algorithms.

  Language:Python30776

• timzatko/Sklearn-Nature-Inspired-Algorithms

  Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.

  Language:Python289

• NiaOrg/NiaPy

  Python microframework for building nature-inspired algorithms. Official docs: https://niapy.org

  Language:Python25877

• numpy/numpy

  The fundamental package for scientific computing with Python.

  Language:Python27.7k9.9k

• rsteca/sklearn-deap

  Use evolutionary algorithms instead of gridsearch in scikit-learn

  Language:Jupyter Notebook771131

• yelboudouri/EmoNeXt

  Code for the paper: "EmoNeXt: an Adapted ConvNeXt for Facial Emotion Recognition"

  Language:Python277

• mmasana/FACIL

  Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.

  Language:Python52499

• srebuffi/iCaRL

  Language:Python24591

• meyerls/aruco-estimator

  Automatic Scale Factor Estimation of 3D Reconstruction in COLMAP Utilizing Aruco Marker

  Language:Python384

• chuong/cattle_identification_action_recognition

  This paper provides codes and a data for our DICTA 2021 paper "Video-based cattle identification and action recognition".

  8

• albumentations-team/albumentations

  Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

  Language:Python14.1k1.6k

• saman-nia/MultiClass-Classification

  Deep Learning VS. Machine learning

  Language:Jupyter Notebook1

• Ivanylson/TCC_LogicTEI

  Trabalho de Conclusão de curso SI/UFJF

  Language:HTML3

• SysCV/sam-hq

  Segment Anything in High Quality [NeurIPS 2023]

  Language:Python3.7k220