Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Brightness-Enhanced Gastrointestinal Endoscopy Image Classification Using CNN-Based Diagnostic Model
Abstract: This study proposes a framework based on a Cycle-Consistent Generative Adversarial Network (CycleGAN) to improve the image brightness and visual continuity of gastrointestinal (GI) ...
Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
+This project focuses on building a Convolutional Neural Network (CNN) using Keras (TensorFlow backend) to classify images into two categories: Dog and Cat. + +The objective is to learn meaningful ...
This study introduces a small apple pre-thinning dataset designed to support the development of intelligent thinning systems by providing reliable data for small apple detection. The dataset comprises ...
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