#transfer-learning

The Real Test Begins After the Course Ends: How education can develop independent thinkers rather…

Some courses are designed to produce good test-takers, while others are built to produce people who continue learning after the course…

DenseNet Explained: Dense Connections for Smarter Deep Learning

In the previous article, we explored InceptionNet, where multiple filter sizes run in parallel to capture rich feature representations.

Integrating a Transfer Learning–Based CoreML Model for Real-Time Camera Inference

In the previous part, the model trained via transfer learning was saved as best_overall.pt. We will convert the higher-performing…

Developing a Document Recognition Model with CoreML through Transfer Learning

One of the biggest challenges in building an AI model is that it requires a massive amount of data. For example, to build a model that…

Building a Real-Time Fire Detection and People Counting System with InceptionV3 and OpenCV

How transfer learning and classical computer vision can work together on edge hardware to save lives

Transfer Learning + TinyML: Building AI-Powered Person Detection on IoT Devices

Master machine learning on edge devices with transfer learning and TinyML. A practical guide to deploying person detection on…

Beyin BT Görüntülerinde Derin Öğrenme ile Kanama Tespiti

Merhaba. Bu yazıda arkadaşlarımla birlikte üzerinde çalıştığımız bir akademik derin öğrenme projesini anlatacağım: beyin BT (bilgisayarlı…

My Model Was 96% Accurate. And I Still Didn’t Trust It.

High accuracy is necessary but not sufficient. Here’s how Grad-CAM revealed what a pneumonia classifier was actually looking at — and why…

化學資訊學入門與實作：遷移學習（Transfer Learning）在分子物性預測的應用

解決小數據集的困境：用預訓練模型提升 QSAR/QSPR 的預測精度

Plant Disease Detection using Transfer Learning 🌱

The main objective of this group project was to create an intelligent solution that can identify plant diseases using image classification…

The Bottleneck: Efficient Transfer Learning on CIFAR-10 using MobileNetV2

Abstract

From Scratch vs Transfer Learning : Hitting the Ground Running from the Midpoint

So, you’ve got a fancy new model and some data. Should you train it from a blank slate (Scratch) or borrow some “brainpower” from a…

Brain Tumor Detection with VGG16: A Complete Guide to Transfer Learning and Fine-Tuning on MRI…

How I built a binary classifier that detects brain tumors from MRI scans using only 253 images — and why the two-phase training strategy is…

AI Developer Interview Assignment: Blur Detection, Computer Vision Fundamentals, and the Reality…

In the last few years, the AI landscape has been dominated by LLMs, generative systems, and agentic workflows. Conversations revolve around…

Xception Transfer Learning in TensorFlow: Build a Ship Classifier

xception transfer learning tensorflow is one of the most practical ways to train a strong image classifier without starting from zero. In…

Transfer Learning in Computer Vision: From Pretrained Models to Production-Ready Systems

Why This Blog Exists (And Why Transfer Learning Is Not Optional)

The AI That Listens to the Wild: 5 Things I Learned at AIMS About Bioacoustics

Kaggle’dan Gerçek Dünyaya: Az Veriyle NLP’nin Hayatta Kalma Rehberi

İlk kez gerçek bir NLP projesiyle karşılaştığımda, Kaggle yarışmalarındaki mükemmel veri setlerinden çok farklı bir dünyada olduğumu fark…

Flexible Application: From Mastery to Adaptive Problem‑Solving

Once a skill or a body of knowledge enters the advanced stage, the practitioner has two primary tasks: first, to achieve flexible…

Transfer Learning with Real World Example

Imagine a kid learning to ride a bicycle. At first, the focus is on balance, steering, and understanding the road. These skills are not…

Transfer Learning That Actually Works: How I Trained a High-Accuracy Image Classifier on Just 300…

A hands-on walkthrough of using pretrained CNNs to build robust models on tiny datasets, complete with data augmentation, fine-tuning…

Understanding Types of Transfer Learning in Deep Learning

Transfer learning is a foundational technique in deep learning that enables models trained on one task to be reused for another. Instead of…

Self-Paced Collaborative and Adversarial Network for Unsupervised Domain Adaptation (비지도 도메인 적응을…

배경 및 개요

Le Transfert Learning appliqué à l’imagerie médicale : une aventure prometteuse

1. Pourquoi le Transfert Learning ?

Transfer Learning on Custom Datasets: Using Your Own Image Folders with PyTorch (with practical…

Training deep networks from scratch can be hard when you have limited data, no powerful GPU, or little time. Transfer learning solves this…

🚀 Fine-Tuning BLIP-2 with LoRA on the Flickr8k Dataset for Image Captioning

📌 Introduction

Transfer Learning com ResNet18: Classificação de Imagens no Dataset Oxford-IIIT Pet

O uso de transfer learning é uma técnica poderosa que permite a reutilização de modelos previamente treinados em tarefas relacionadas…

Mastering the Art of Training One Large Language Model to Precisely Mimic the Another LLM: A Deep…

I write about a wide range of topics, so feel free to check out my other articles if you have the time.

Transfer Learning Metoduyla Öneri Motoru Geliştirmek

…benzer ürünleri tavsiye eden bir öneri motorunu Transfer Learning metodu ile yapmanın aslında ne kadar basit olduğunu göstereceğim.

CNN Anatomy: Revealing Layer Output Dynamics

One of the most significant applications of neural networks lies in the domain of Convolutional Neural Networks, commonly known as CNNs…

NASA RULMAN VERİSETİYLE GELİŞMİŞ DERİN TRANSFER ÖĞRENME YÖNTEMLERİ KULLANARAK RULMAN HATALARININ…

Merhaba, yüksek lisans tezimin özet kısmını sizlerle paylaşmak istedim. Eğer ilgilenirseniz detaylar ile ilgili bir linkte paylaştım.

Convolutional Neural Network — Lesson 14: Advanced Topics in CNNs

Introduction to 3D Convolutional Networks

Transfer Learning Using DenseNet201

Transfer learning using DenseNet-201

Image caption by transfer learning — Flickr8k data

Introduction