Ongoing research into AI agent framework security identified an exploit chain in AutoGen Studio (AutoGen’s open-source prototyping user interface) that allows untrusted web content rendered by a ...
This GitHub Repository was produced to share material relevant to the Journal paper Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer ...
Abstract: Current deep learning-based reconstruction models for accelerated multi-coil magnetic resonance imaging (MRI) mainly focus on subsampled k-space data of single modality using convolutional ...
The suggested framework uses YOLOv8s to automatically eliminate road backgrounds, reducing interference and increasing the precision of object detection. This fusion approach uses a CNN encoder and a ...
This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for classification and ...
Sclera-TransFuse: Fusing Vision Transformer and CNN for Accurate Sclera Segmentation and Recognition
Abstract: This paper investigates a deep learning based unified framework for accurate sclera segmentation and recognition, named Sclera-TransFuse. Unlike previous CNN-based methods, our framework ...
This paper presents a mini-review of recent works in Salient Object Detection (SOD). First, We introduce SOD and its application in image processing tasks and applications. Following this, we discuss ...
Tumor-infiltrating lymphocytes, specialized immune cells, are considered an important biomarker in cancer analysis. Automated lymphocyte detection is challenging due to its heterogeneous morphology, ...
This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results