Faster R-CNN
PulseAugur coverage of Faster R-CNN — every cluster mentioning Faster R-CNN across labs, papers, and developer communities, ranked by signal.
7 day(s) with sentiment data
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AI models evaluated for African crop detection in new study
A new study published on arXiv evaluates six object detection models for agricultural applications, specifically focusing on plant detection in real-world African farming conditions. The research utilized the AgriAISeg …
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New SkySeaLand benchmark targets satellite object detection challenges
Researchers have introduced SkySeaLand, a new benchmark dataset designed for satellite object detection, particularly focusing on wide-format scenes and small targets. The dataset comprises 1,307 high-resolution satelli…
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New black-box attack method ColorFD targets remote sensing object detectors
Researchers have developed ColorFD, a novel black-box physical adversarial attack method designed for remote sensing object detectors. This method utilizes multiple pure-color patches, optimizing their positions and col…
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Deep learning model advances utility pole and sign detection
Researchers have developed a deep learning framework for detecting, segmenting, and estimating the lean angle of utility poles, as well as classifying attached warning signs. The system, based on a modified Detection Tr…
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New open dataset OSSDD released for Sentinel-1 ship detection
Researchers have introduced OSSDD, a new open dataset designed for training neural networks to detect ships in Synthetic Aperture Radar (SAR) images. This dataset, built upon the OpenSARShip 1.0 dataset, provides 15,197…
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Pathology Foundation Models Show Promise for Mitotic Figure Detection
Researchers have explored the effectiveness of pathology foundation models (FMs) as encoders for mitotic figure detection, moving beyond their typical use in classification tasks. The study compared several FMs, includi…
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New method generates geometric 2D scene graphs for assembly analysis
Researchers have developed a new method for generating geometric 2D scene graphs, which represent assembly relationships between components. This approach utilizes the output of a Faster R-CNN model to create geometric …
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LVLMs show promise for SOTIF-compliant object detection in autonomous vehicles · 2 sources tracked
A new research paper evaluates Large Vision-Language Models (LVLMs) for 2D object detection in automated driving systems, focusing on Safety Of The Intended Functionality (SOTIF) conditions. The study used the PeSOTIF d…
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MalariAI framework enhances malaria diagnosis with cell segmentation and explainability
Researchers have developed MalariAI, a novel two-stage framework designed to improve the accuracy and reliability of automated malaria diagnosis from blood smear microscopy. This system addresses key limitations in exis…
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DefocusTrackerAI uses YOLOv9 for particle image detection
Researchers have developed DefocusTrackerAI, a new deep-learning framework for automatically detecting and estimating the positions of defocused particle images. The system utilizes a YOLOv9 architecture, which demonstr…
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New AI method highlights PCB defects using reference images
Researchers have developed RefDiffNet, a novel input enhancement block designed to improve the detection of subtle defects on printed circuit boards (PCBs). This lightweight module works by comparing a defective PCB ima…
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Meta AI's Detectron2 framework simplified for object detection
This tutorial offers a simplified guide to Meta AI's Detectron2 framework for computer vision tasks. It demonstrates how to construct a Faster R-CNN pipeline, a method commonly used for accurate object detection. The re…
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HeroCrystal framework advances privacy-preserving multi-camera AI surveillance
Researchers have developed HeroCrystal, a new framework for privacy-preserving object detection in multi-camera surveillance systems. This system uses synthetic data generation via diffusion models to augment datasets w…
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GPT Driver uses AI and vision to automate mobile app testing
MobileBoost has launched GPT Driver, an AI-powered tool designed to automate end-to-end testing for mobile applications. The platform allows users to define tests using natural language, leveraging LLM reasoning and com…