Results 81 to 90 of about 1,485,416 (350)
Focus-and-Detect: A small object detection framework for aerial images
Signal Processing: Image Communication, 2022 Despite recent advances, object detection in aerial images is still a challenging task. Specific problems in aerial images makes the detection problem harder, such as small objects, densely packed objects, objects in different sizes and with different orientations.
Onur Can Koyun +3 more
openaire +3 more sources
Hybrid Intersection Over Union Loss for a Robust Small Object Detection in Low-Light Conditions
IEEE AccessIn computer vision, most existing works about object detection focus on detecting objects in the good lighting conditions instead of low-light conditions.
Twahir Kiobya +3 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Surveillance imaging aims to detect tumour relapse before symptoms develop, but it's unclear whether earlier detection of relapse leads to better outcomes in children and young people (CYP) with medulloblastoma and ependymoma. This systematic review aims to identify relevant literature to determine the efficacy of surveillance magnetic ...
Lucy Shepherd +3 more
wiley +1 more source
SBNet: Sparse Blocks Network for Fast Inference
, 2018 Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications.
Pokrovsky, Andrei +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Despite their increased risk for functional impairment resulting from cancer and its treatments, few adolescents and young adults (AYAs) with a hematological malignancy receive the recommended or therapeutic dose of exercise per week during inpatient hospitalizations.
Jennifer A. Kelleher +8 more
wiley +1 more source
LSDA: Large Scale Detection Through Adaptation [PDF]
, 2014 A major challenge in scaling object detection is the difficulty of obtaining labeled images for large numbers of categories. Recently, deep convolutional neural networks (CNNs) have emerged as clear winners on object classification benchmarks, in part ...
Darrell, Trevor +7 more
core
Object Detection based on Region Decomposition and Assembly
, 2019 Region-based object detection infers object regions for one or more categories in an image. Due to the recent advances in deep learning and region proposal methods, object detectors based on convolutional neural networks (CNNs) have been flourishing and ...
Bae, Seung-Hwan
core +1 more source
Dynamic Tiling: A Model-Agnostic, Adaptive, Scalable, and Inference-Data-Centric Approach for Efficient and Accurate Small Object Detection [PDF]
, 2023 Son The Nguyen +2 more
openalex +1 more source
Lightweight Small Object Detection Algorithm for Aerial Photography Based on Improved YOLOv8n: PECS-YOLO [PDF]
Jisuanji gongchengIn Unmanned Aerial Vehicle (UAV) aerial photography, targets are usually small targets with dense distribution and unobvious features, and the object scale varies greatly. Therefore, the problems of missing detection and false detection are easy to occur
WANG Shumeng, XU Huiying, ZHU Xinzhong, HUANG Xiao, SONG Jie, LI Yi
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu +20 more
wiley +1 more source