IEEE

Adversial Learning Through GAN and Feature Extraction Through CNN for Deep Fake Detection

Abstract: Deepfake technology, using deep learning, creates highly realistic yet artificial media, creating challenges for security and privacy. Convolutional Neural Networks (CNNs) play a crucial ...
Android Police

New Even G2 smartglasses feature works like a cheat code for meetings

Andy is a seasoned technology journalist with more than 15 years experience in the mobile industry, writing for Digital Trends, Wired, and more. During that time he has reviewed hundreds of ...
IEEE

SCAFNet: A Semantic Compensated Adaptive Fusion Network for Remote Sensing Images Change Detection

Abstract: Current CNN–Transformer hybrid methods for remote sensing change detection aim to address the limitations of the CNNs’ constrained receptive fields and the Transformers’ local detail ...
IEEE

PrefixCAN-Signal: PrefixSpan-based Automatic Controller Area Network Signal Extraction

Abstract: Modern vehicles rely heavily on Controller Area Network (CAN) communication for time-critical functions such as engine control and powertrain management. As vehicles become increasingly ...
IEEE

SEGS-MobileNetV2: An Enhanced Lightweight CNN for Efficient Feature Representation in Industrial Defect Classification

Abstract: Industrial defect images are often low-resolution and exhibit subtle texture variations, making fine-grained feature extraction particularly challenging. To address these issues, we propose ...
IEEE

Dual-Stage Feature Optimization: Fault Classification Combining Signal Decomposition and LightGBM

Abstract: To improve the fault diagnosis accuracy of synchronous condenser bearings, this study proposes an intelligent diagnostic method based on multi-domain feature fusion. First, vibration signals ...
IEEE

Transformer-CNN Hybrid Architecture for Heart Disease Risk Stratification: Leveraging Self-Attention Mechanisms and Convolutional Feature Extraction

Abstract: Heart disease is the leading global cause of death, requiring accurate and interpretable prediction models. This thesis proposes a Transformer-CNN hybrid that integrates CNN local feature ...
GitHub

Multi-platform point cloud analysis — registration, segmentation, surface reconstruction, and feature extraction for aerial, terrestrial, and UAV LiDAR.

Point cloud tooling in Python is fragmented. laspy reads files. Open3D visualizes them. PDAL pipelines transform them. But nothing treats acquisition platform as a first-class concept — and platform ...
KTVZ

The world’s most valuable company just sent another signal that AI agents are going to be everywhere

(CNN) — Tech giant Nvidia, the world’s most valuable company and the poster child of the AI boom, is banking its future on the rise of AI agents. The company on Monday announced a slew of software and ...
IEEE

Short-term Load Forecasting of Residential Power Users Based on SCAE-CNN-GRU Hybrid Model

Abstract: Accurate short-term load forecasting for residential user groups is crucial for modern power systems. To overcome the limitations of traditional models, this study proposes a hybrid model ...
IEEE

Edge Intelligence for Speech: Evaluating Model Performance, Feature Extraction and Signal Fidelity on Commodity Hardware

Abstract: This paper presents a comprehensive examination of speech analysis techniques, focusing on their applicability and performance in edge computing environments, particularly on single-board ...