Results 61 to 70 of about 318,999 (276)
Crowd Counting with Density Adaption Networks
CoRR, 2018 Crowd counting is one of the core tasks in various surveillance applications. A practical system involves estimating accurate head counts in dynamic scenarios under different lightning, camera perspective and occlusion states. Previous approaches estimate head counts despite that they can vary dramatically in different density settings; the crowd is ...
Li Wang 0033 +5 more
openaire +2 more sources
AAA+ protein unfoldases—the Moirai of the proteome
FEBS Letters, EarlyView.AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley +1 more source
A Deeply-Recursive Convolutional Network For Crowd Counting [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 The estimation of crowd count in images has a wide range of applications such as video surveillance, traffic monitoring, public safety and urban planning. Recently, the convolutional neural network (CNN) based approaches have been shown to be more effective in crowd counting than traditional methods that use handcrafted features.
Xinghao Ding +4 more
openaire +2 more sources
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
Molecular Oncology, EarlyView.This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source
Crowd counting via Multi-Scale Adversarial Convolutional Neural Networks
Journal of Intelligent Systems, 2020 The purpose of crowd counting is to estimate the number of pedestrians in crowd images. Crowd counting or density estimation is an extremely challenging task in computer vision, due to large scale variations and dense scene.
Zhu Liping +4 more
doaj +1 more source
Why human connection is the true metric of research success
FEBS Open Bio, EarlyView.Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan +3 more
wiley +1 more source
A COMPARATIVE STUDY OF CROWD COUNTING AND PROFILING THROUGH VISUAL AND NON-VISUAL SENSORS [PDF]
Acta Informatica Malaysia, 2019 In this paper we present a comparative critical study of visual and non-visual sensors used in crowd behavior analysis. The understanding of crowd has main impact of the analysis how much they support the system is the key factor of the analysis.
Jugal Kishor Gupta, S.K. Gupta
doaj +1 more source
AVMSN: An Audio-Visual Two Stream Crowd Counting Framework Under Low-Quality Conditions
IEEE Access, 2021 Crowd counting is considered as the essential computer vision application that uses the convolutional neural network to model the crowd density as the regression task.
Ruihan Hu +8 more
doaj +1 more source
Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation
, 2019 State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density in the image plane. While useful for this purpose, this image-plane density has no immediate physical meaning because it is subject to ...
Fua, Pascal +3 more
core +1 more source
RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
FEBS Open Bio, EarlyView.RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour +2 more
wiley +1 more source