A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms
Wildfire is one of the most critical natural disasters that threaten wildlands and forest
resources. Traditional firefighting systems, which are based on ground crew inspection …
resources. Traditional firefighting systems, which are based on ground crew inspection …
A survey on deep learning-based architectures for semantic segmentation on 2d images
Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
Lsknet: A foundation lightweight backbone for remote sensing
Remote sensing images pose distinct challenges for downstream tasks due to their inherent
complexity. While a considerable amount of research has been dedicated to remote sensing …
complexity. While a considerable amount of research has been dedicated to remote sensing …
Singular value fine-tuning: Few-shot segmentation requires few-parameters fine-tuning
Freezing the pre-trained backbone has become a standard paradigm to avoid overfitting in
few-shot segmentation. In this paper, we rethink the paradigm and explore a new …
few-shot segmentation. In this paper, we rethink the paradigm and explore a new …
Context-aware poly (a) signal prediction model via deep spatial–temporal neural networks
Polyadenylation [Poly (A)] is an essential process during messenger RNA (mRNA)
maturation in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the …
maturation in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the …
Weighted average ensemble deep learning model for stratification of brain tumor in MRI images
Brain tumor diagnosis at an early stage can improve the chances of successful treatment
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …
Cascade multiscale residual attention cnns with adaptive roi for automatic brain tumor segmentation
A brain tumor is one of the fatal cancer types which causes abnormal growth of brain cells.
Earlier diagnosis of a brain tumor can play a vital role in its treatment; however, manual …
Earlier diagnosis of a brain tumor can play a vital role in its treatment; however, manual …
Fractional Fourier image transformer for multimodal remote sensing data classification
With the recent development of the joint classification of hyperspectral image (HSI) and light
detection and ranging (LiDAR) data, deep learning methods have achieved promising …
detection and ranging (LiDAR) data, deep learning methods have achieved promising …
TransKD: Transformer knowledge distillation for efficient semantic segmentation
Semantic segmentation benchmarks in the realm of autonomous driving are dominated by
large pre-trained transformers, yet their widespread adoption is impeded by substantial …
large pre-trained transformers, yet their widespread adoption is impeded by substantial …
Source-free open compound domain adaptation in semantic segmentation
In this work, we introduce a new concept, named source-free open compound domain
adaptation (SF-OCDA), and study it in semantic segmentation. SF-OCDA is more …
adaptation (SF-OCDA), and study it in semantic segmentation. SF-OCDA is more …