News

IEEE1d
Automated Text Extraction and Classification from Images using Multi-Layer Perceptron(MLP)
Abstract: This research paper presents a comprehensive approach for extracting and classifying text from images using computer vision and deep learning techniques. We demonstrate a step-by-step ...
IEEE3d
Image Manipulation Localization Using Attentional Cross-Domain CNN Features
To tackle the challenging image tampering detection problem, this article presents an attentional cross-domain deep architecture, which can be trained end-to-end. This architecture is composed of ...
IEEE5d
Neutron-induced Faults on CNN for Aerial Image Classification on SRAM-based FPGA Using Softcore GPU and HLS
Abstract: This work evaluates neutron-induced soft errors in an image classification all-convolutional neural ... shown that the HLS architecture presents better reliability than the CNN running on ...
IEEE5d
An Approach to Detect COVID-19 Disease from CT Scan Images using CNN - VGG16 Model
Machine Learning Techniques, specifically Convolutional Neural Networks (CNN) VGG16 model is used to train dataset and use trained model to predict, have been developed in this project. Four distinct ...
IEEE8d
Classification of Style in Fine-Art Paintings Using Transfer Learning and Weighted Image Patches
Experimental validation based on two standard art classification datasets and six different pre-trained convolutional neural network (CNN) models (AlexNet, VGG-16, VGG-19, GoogLeNet, ResNet-50 and ...
IEEE15d
An automated CNN recommendation system for image classification tasks
Abstract: Nowadays the CNN is widely used in practical applications for image classification task. However the design of the CNN model is very professional work and which is very difficult for ...
IEEE15d
Novel Method for Bone Cancer Detection using Segmentation and Classification with CNN
Using CNNs (Convolutional Neural Networks ... demonstrating the powerful capabilities of deep learning techniques. When analyzing images, for bone cancer detection CNN s selective capabilities are ...
IEEE19d
ES-GP: An Ensemble Surrogate-Assisted Genetic Programming Approach to Image Classification
Abstract: Genetic Programming (GP) is a promising evolutionary machine learning technique for image classification, known for its ability to evolve flexible, effective, and interpretable models.
techxplore19d
AI model classifies images with a hierarchical tree from broad to specific
H-CAST was trained and tested using ARC High Performance Computing at U-M. UC Berkeley, MIT and Scaled Foundations also contributed to this research. More information: Seulki Park, et al. Visually ...
CNN19d
Incredible images showcase scientists at work
The winning images show scientists in cold and warmer climates. One features researchers boring an ice core in the archipelago of Svalbard, while another shows a biologist holding tiny froglets in ...
IEEE21d
Classification of Medical Images with Synergic Graph Convolutional Networks
A synergic graph convolutional networks (SGCN) model is proposed for image classification. This model is based on convolutional neural networks on graphs with fast localized spectral filtering. In our ...
IEEE21d
An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals
Their precise segmentation within hyperspectral images (HSIs ... instance segmentation using models previously trained on RGB images. A comparative analysis of three Mask Region-based Convolutional ...