[HTML][HTML] A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas
J Terven, DM Córdova-Esparza… - Machine Learning and …, 2023 - mdpi.com
YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …
and video monitoring applications. We present a comprehensive analysis of YOLO's …
Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in developing new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
Deep spectral methods: A surprisingly strong baseline for unsupervised semantic segmentation and localization
L Melas-Kyriazi, C Rupprecht… - Proceedings of the …, 2022 - openaccess.thecvf.com
Unsupervised localization and segmentation are long-standing computer vision challenges
that involve decomposing an image into semantically-meaningful segments without any …
that involve decomposing an image into semantically-meaningful segments without any …
Simple copy-paste is a strong data augmentation method for instance segmentation
Building instance segmentation models that are data-efficient and can handle rare object
categories is an important challenge in computer vision. Leveraging data augmentations is a …
categories is an important challenge in computer vision. Leveraging data augmentations is a …
Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement
Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment.
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Attentional feature fusion
Feature fusion, the combination of features from different layers or branches, is an
omnipresent part of modern network architectures. It is often implemented via simple …
omnipresent part of modern network architectures. It is often implemented via simple …
Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation
Low-level details and high-level semantics are both essential to the semantic segmentation
task. However, to speed up the model inference, current approaches almost always sacrifice …
task. However, to speed up the model inference, current approaches almost always sacrifice …
A survey on instance segmentation: state of the art
Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …
digital image inference. It not only provides the classes of the image objects, but also …
Yolov4: Optimal speed and accuracy of object detection
There are a huge number of features which are said to improve Convolutional Neural
Network (CNN) accuracy. Practical testing of combinations of such features on large …
Network (CNN) accuracy. Practical testing of combinations of such features on large …
Asymmetric contextual modulation for infrared small target detection
Single-frame infrared small target detection remains a challenge not only due to the scarcity
of intrinsic target characteristics but also because of lacking a public dataset. In this paper …
of intrinsic target characteristics but also because of lacking a public dataset. In this paper …