This is the official repository of the papers "Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers" and "Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters".

Support project for my Bachelor's thesis @ Unifi - Converting Oxford5k and Paris6k into datasets suitable for object detection tasks. This repository contains scripts to create XML (PASCAL VOC format) and JSON (COCO format) annotations from .pkl files, enabling the training of an SSD/MobileNet object detection model.

Image Content Filtering Using CNN and Transfer Learning

autoupdate paper list

Comparing MobileNet and EfficientNet on Glaucoma Detection

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

Gather research papers, corresponding codes (if having), reading notes and any other related materials about Hot🔥🔥🔥 fields in Computer Vision based on Deep Learning.

Image Classification Web App for Tourists of the City of Münster.

Collection of awesome test-time (domain/batch/instance) adaptation methods

The official implementation of paper: "Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning"

Fast and Accurate ML in 3 Lines of Code

This project aims to explore the optimization and transferability of knowledge using Topological Data Analysis (TDA) and Convolutional Neural Networks (CNN).

common wrapper for securities API

interface to geneformer

Import/export ONNX models

Open Source installer, updater for Trainer Studio under Apache 2.0 License

MONITOR THE EMPLOYEE'S EMOTIONAL WELL-BEING WITH PRE-TRAINED NEURAL NETWORK GOOGLENET USING THE FER2013 DATASET

ECCV 2022 Workshop: AI-enabled Medical Image Analysis – Digital Pathology & Radiology/COVID19 : An easy-to-understand and lightweight Transfer Learning-based solutions for COVID-19 diagnosis

Automatic feature extraction and node role assignment for transfer learning on graphs (ReFeX & RolX)

Model analisis sentimen berbasis IndoBERT yang dapat memprediksi sentimen dalam teks berbahasa Jawa Ngoko Lugu