IEEE

Removal Then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection

Abstract: In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of ...
IEEE

Spatial-Frequency Collaborative Learning for Camouflaged Object Detection

Abstract: Camouflaged object detection (COD) is a challenging task that struggles to accurately detect the objects concealed in the surrounding environment. This is largely attributed to the intrinsic ...
IEEE

UniROD: Unified Radar Object Detection with MAE-pretrained CNN-Transformer Fusion

Millimeter-wave radar object detection has become pivotal for autonomous driving systems requiring all-weather reliability. While conventional CFAR methods face limitations in classification ...
IEEE

Ensemble of Fast R-CNN with Bi-LSTM for Object Detection

Abstract: Object detection is a critical task in computer vision, with applications ranging from autonomous driving to medical imaging. Traditional object detection models, such as Fast R-CNN, have ...
CNN

Astronomers detect a solar system they say should not be possible

An exoplanetary system about 116 light-years from Earth could flip the script on how planets form, according to researchers who discovered it using telescopes from NASA and the European Space Agency, ...
IEEE

Adaptive Receptive Field Network for Small Objects Detection in Remote Sensing Images

Abstract: Small object detection in remote sensing images is severely hampered by the significant scale variation even among small objects. Conventional methods often rely on a static receptive field ...
IEEE

TCINet: Transformer–CNN Interaction Network for Space Noncooperative Object Saliency Detection

Abstract: Space noncooperative object detection (SNCOD) is an essential part of space situation awareness. The localization and segmentation capabilities of the salient object detection (SOD) method ...
IEEE

An Object Detection Algorithm of Literatures’ Key Information Based on Optimized Cascade R-CNN

Abstract: To address the problems of relying on electronic repositories and being vulnerable to network influence in obtaining key information of literature in mainstream literature management ...
IEEE

A Verilog based Approach for Object Detection using CNN

Abstract: A Convolutional Neural Network (CNN) are a class of artificial neural networks specifically designed to process data with a grid-like topology, such as images, making them well-suited for ...
Ars Technica

TikTok users “absolutely justified” in fearing MAGA makeover, experts say

TikTok wants users to believe that errors blocking uploads of anti-ICE videos or direct messages mentioning Jeffrey Epstein are due to technical errors—not the platform shifting to censor content ...
IEEE

Active Learning for Object Detection With Vectorized Dual Pseudo Loss and Multiple Instance Offset Constraint

Abstract: Existing active learning methods for object detection face challenges, such as the lack of ground truth labels for regression loss, insufficient representation of unlabeled instance samples ...