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Hi there. This is Erik Valle, a graduate student at Tsinghua University.

🌍 I am working on Transfer Learning, including multi-source domain adaptation, federated learning, and fine-tuning for Automatic Optical Inspection and Autonomous Vehicles.

👯 I am looking to collaborate on computer vision research and transfer learning stuff, so please message me.

Connect with me on:

🏢 LinkedIn

💡 ResearchGate

🤔 StackOverflow

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Erik Valle's Projects

orb_slam2 icon orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

paddledetection icon paddledetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

poibin icon poibin

Poisson Binomial Probability Distribution for Python

prophet icon prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

ptis icon ptis

This repository contains the project proposal,code and final report for the implementation of the paper "Parallax Tolerant Image Stitching"(link :"https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6909813").

pv_defect_detection icon pv_defect_detection

Multi-label defect detection for Solar Cells from Electroluminescence images of the modules, using Deep Learning

pylabel icon pylabel

Python library to transform, analyze, and visualize computer vision annotations.

pytorch-gan icon pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

recall icon recall

Official TensorFlow implementation of "RECALL: Replay-based Continual Learning in Semantic Segmentation", ICCV 2021

rohsi icon rohsi

Source code of "Hyperspectral Image Classification Using Random Occlusion Data Augmentation"

rtlaoi-dd icon rtlaoi-dd

Relational-based Transfer Learning for Automatic Optical Inspection based on domain discrepancy

sdr icon sdr

PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

smote_variants icon smote_variants

A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

ssda-yolo icon ssda-yolo

Codes for my paper "SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection"

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