A CNN-transformer network with multiscale context aggregation for fine-grained cropland change detection
Nonagriculturalization incidents are serious threats to local agricultural ecosystem and
global food security. Remote sensing change detection (CD) can provide an effective …
global food security. Remote sensing change detection (CD) can provide an effective …
Progressive semantic-visual mutual adaption for generalized zero-shot learning
Abstract Generalized Zero-Shot Learning (GZSL) identifies unseen categories by knowledge
transferred from the seen domain, relying on the intrinsic interactions between visual and …
transferred from the seen domain, relying on the intrinsic interactions between visual and …
Fine-grained visual classification via internal ensemble learning transformer
Recently, vision transformers (ViTs) have been investigated in fine-grained visual
recognition (FGVC) and are now considered state of the art. However, most ViT-based works …
recognition (FGVC) and are now considered state of the art. However, most ViT-based works …
Lesion-aware visual transformer network for Paddy diseases detection in precision agriculture
Precision agriculture, driven by advancements in sensing technologies and data analytics,
offers promising solutions for addressing challenges in paddy disease management. Paddy …
offers promising solutions for addressing challenges in paddy disease management. Paddy …
Multi-source aggregation transformer for concealed object detection in millimeter-wave images
The active millimeter wave scanner has been widely used for detecting objects concealed
underneath a person's clothing in the field of security inspection and anti-terrorism …
underneath a person's clothing in the field of security inspection and anti-terrorism …
The image data and backbone in weakly supervised fine-grained visual categorization: A revisit and further thinking
Weakly-supervised fine-grained visual categorization (FGVC) aims to achieve subclass
classification within the same large class using only label information. Compared to general …
classification within the same large class using only label information. Compared to general …
Part-object progressive refinement network for zero-shot learning
Zero-shot learning (ZSL) recognizes unseen images by sharing semantic knowledge
transferred from seen images, encouraging the investigation of associations between …
transferred from seen images, encouraging the investigation of associations between …
Class incremental learning for light-weighted networks
Despite deep neural networks (DNNs) show impressive performance across diverse tasks,
they suffer from catastrophic forgetting when dealing with continuous data streams …
they suffer from catastrophic forgetting when dealing with continuous data streams …
PSDPM: Prototype-based Secondary Discriminative Pixels Mining for Weakly Supervised Semantic Segmentation
Abstract Image-level Weakly Supervised Semantic Segmentation (WSSS) has received
increasing attention due to its low annotation cost. Class Activation Mapping (CAM) …
increasing attention due to its low annotation cost. Class Activation Mapping (CAM) …
Continual Segmentation with Disentangled Objectness Learning and Class Recognition
Most continual segmentation methods tackle the problem as a per-pixel classification task.
However such a paradigm is very challenging and we find query-based segmenters with …
However such a paradigm is very challenging and we find query-based segmenters with …