North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Evaluating Pretrained Deep Learning Models for Image Classification Against Individual and Ensemble Adversarial Attacks

Abstract: The robustness of Deep Neural Networks (DNNs) against adversarial attacks is an important topic in the area of deep learning. To fully investigate the robustness of DNNs, this study examines ...
techxplore

AI model classifies images with a hierarchical tree from broad to specific

A new AI model, H-CAST, groups fine details into object-level concepts as attention moves from lower to high layers, outputting a classification tree—such as bird, eagle, bald eagle—rather than ...
Frontiers

Diagnosis of pneumonia from chest X-ray images using YOLO deep learning

To address this, we propose a novel pneumonia diagnosis method using the Fast-YOLO deep learning network that we introduced. First, we constructed a pneumonia dataset containing five categories and ...
Scientific Research Publishing

Credit Score Classification Using Advanced Machine Learning: A Comprehensive Approach ()

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
Frontiers

Next-generation approach to skin disorder prediction employing hybrid deep transfer learning

Table 1 summarizes the key contributions, findings, and limitations of recent studies. These studies highlight the significant progress made in applying deep learning to skin disease classification ...
IEEE

A Hyperspectral Classification Method Based on Deep Learning and Dimension Reduction for Ground Environmental Monitoring

Abstract: Hyperspectral remote sensing images exhibit high dimensionality, a large volume of data, and significant redundant information. Before using deep learning methods for ground monitoring and ...