Face mask detection in smart cities using deep and transfer learning: Lessons learned from the COVID-19 pandemic
After different consecutive waves, the pandemic phase of Coronavirus disease 2019 does
not look to be ending soon for most countries across the world. To slow the spread of the …
not look to be ending soon for most countries across the world. To slow the spread of the …
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging
Molecular classification has transformed the management of brain tumors by enabling more
accurate prognostication and personalized treatment. However, timely molecular diagnostic …
accurate prognostication and personalized treatment. However, timely molecular diagnostic …
ICIF-Net: Intra-scale cross-interaction and inter-scale feature fusion network for bitemporal remote sensing images change detection
Change detection (CD) of remote sensing (RS) images has enjoyed remarkable success by
virtue of convolutional neural networks (CNNs) with promising discriminative capabilities …
virtue of convolutional neural networks (CNNs) with promising discriminative capabilities …
Query2label: A simple transformer way to multi-label classification
This paper presents a simple and effective approach to solving the multi-label classification
problem. The proposed approach leverages Transformer decoders to query the existence of …
problem. The proposed approach leverages Transformer decoders to query the existence of …
Coarse-to-fine sparse transformer for hyperspectral image reconstruction
Many learning-based algorithms have been developed to solve the inverse problem of
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
Unihcp: A unified model for human-centric perceptions
Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …
person re-identification, etc.) play a key role in industrial applications of visual models. While …
Integrative few-shot learning for classification and segmentation
We introduce the integrative task of few-shot classification and segmentation (FS-CS) that
aims to both classify and segment target objects in a query image when the target classes …
aims to both classify and segment target objects in a query image when the target classes …
Transformer-based dual relation graph for multi-label image recognition
The simultaneous recognition of multiple objects in one image remains a challenging task,
spanning multiple events in the recognition field such as various object scales, inconsistent …
spanning multiple events in the recognition field such as various object scales, inconsistent …
Large loss matters in weakly supervised multi-label classification
Weakly supervised multi-label classification (WSML) task, which is to learn a multi-label
classification using partially observed labels per image, is becoming increasingly important …
classification using partially observed labels per image, is becoming increasingly important …
Coarse-to-fine feature mining for video semantic segmentation
The contextual information plays a core role in semantic segmentation. As for video
semantic segmentation, the contexts include static contexts and motional contexts …
semantic segmentation, the contexts include static contexts and motional contexts …