News

IEEE20h
An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals - IEEE Xplore
The most vulnerable parts of tomatoes are the tips of the sepals, which are the primary entry points for fungal spores. Their precise segmentation within hyperspectral images (HSIs) plays a pivotal ...
IEEE2d
A Comparative Study of CNN and Transformer Models for Image Recognition in Autonomous Driving - IEEE Xplore
An autonomous driving system requires efficient image recognition to interpret the environment, detect obstacles, and make real-time decisions. This study compares Convolutional Neural Networks (CNNs) ...
IEEE2d
Two-Step CNN Framework for Text Line Recognition in Camera-Captured Images - IEEE Xplore
In this paper, we introduce an “on the device” text line recognition framework that is designed for mobile or embedded systems. We consider per-character segmentation as a language-independent problem ...
IEEE3d
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution - IEEE Xplore
Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, they have not yet ...
Lines To Designs on MSN4d
Transform AI Images into 3D Models Meshy + After Effects Tutorial)
Learn how to convert AI-generated images into stunning 3D models using Meshy and After Effects in this step-by-step tutorial. Perfect for creators looking to add depth and motion to their designs. #3D ...
IEEE4d
Face Image Scanning for Differentiation of Child/Adult images using a CNN-Based Model - IEEE Xplore
Differentiating child and adult images is a crucial requirement for many applications. This paper proposes an approach using a Convolutional Neural Network (CNN) model to distinguish between ...
IEEE4d
Quaternion CNN With Salient Features for Color Image Denoising
Deep convolutional neural networks have significantly advanced color image denoising. However, existing models often apply grayscale denoising techniques to color images without accounting for ...
IEEE4d
BEFNet: A Hybrid CNN-Mamba Architecture for Accurate Skin Lesion Image Segmentation - IEEE Xplore
Accurate image segmentation of skin lesions is crucial for the detection and treatment of skin cancer. Based on the modern state space model Mamba, a novel hybrid CNN-Mamba network (BEFNet) is ...
IEEE6d
A Dilated CNN Model for Image Classification - IEEE Xplore
The dilated convolution algorithm, which is widely used for image segmentation, is applied in the image classification field in this paper. In many traditional image classification algorithms, ...
IEEE6d
CTCNet: A CNN-Transformer Dual Branch Network for Sand Dune Image Segmentation - IEEE Xplore
Dune images typically display intricate details and relatively uniform spectral characteristics, making them a unique challenge for image segmentation tasks. Due to the limitations of traditional ...
IEEE8d
Hyperspectral Image Band Selection Based on CNN Embedded GA (CNNeGA) - IEEE Xplore
Hyperspectral images (HSIs) are a powerful source of reliable data in various remote sensing applications. But due to the large number of bands, HSI has information redundancy, and methods are often ...
IEEE8d
Multi-Feature-Based Bilinear CNN for Single Image Dehazing
Image dehazing has been a great challenge in the process of adjusting haze images. In this paper, an effective and accurate dehazing method based on atmospheric scattering model is proposed. Since the ...