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 ...
1 Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, Bangladesh. 2 Department of Electrical and Electronics Engineering, American International ...
Abstract: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...
1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...
• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).
Classifying corn varieties presents a significant challenge due to the high-dimensional characteristics of hyperspectral images and the complexity of feature extraction, which hinder progress in ...
Built a deep CNN for multi-class sports image classification using a Kaggle dataset. Tuned hyperparameters (layers, dropout, optimizer, batch size, learning rate, weight decay) and trained with early ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback