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Found 13 papers, 9 papers with code
FAD-SAR: A Novel Fishing Activity Detection System via Synthetic Aperture Radar Images Based on Deep Learning Method
This paper proposes a deep learning-based system for detecting fishing activities.
Flood Data Analysis on SpaceNet 8 Using Apache Sedona
This platform aims to enhance the efficiency of error analysis, a critical aspect of improving flood damage detection accuracy.
YOLOv9 for Fracture Detection in Pediatric Wrist Trauma X-ray Images
The introduction of YOLOv9, the latest version of the You Only Look Once (YOLO) series, has led to its widespread adoption across various scenarios.
Ranked #2 on
Object Detection
on GRAZPEDWRI-DX
YOLOv8-AM: YOLOv8 with Attention Mechanisms for Pediatric Wrist Fracture Detection
Therefore, we combine ResBlock and GAM, introducing ResGAM to design another new YOLOv8-AM model, whose mAP 50 value is increased to 65. 0%.
Ranked #1 on
Object Detection
on 100STYLE
(using extra training data)
CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization
This work compares the performance of the proposed method with other state-of-the-art (SOTA) methods on DIBCO and H-DIBCO ((Handwritten) Document Image Binarization Competition) datasets.
Ranked #4 on
Binarization
on DIBCO 2013
Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 Algorithm
To enable surgeons to use our model for fracture detection on pediatric wrist trauma X-ray images, we have designed the application "Fracture Detection Using YOLOv8 App" to assist surgeons in diagnosing fractures, reducing the probability of error analysis, and providing more useful information for surgery.
Ranked #9 on
Object Detection
on GRAZPEDWRI-DX
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
We apply this strategy to SwinIR and present a new model, which named SwinOIR (Object Image Restoration Using Swin Transformer).
Ranked #9 on
Image Super-Resolution
on BSD100 - 3x upscaling
Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks
The efficient segmentation of foreground text information from the background in degraded color document images is a critical challenge in the preservation of ancient manuscripts.
Ranked #2 on
Binarization
on H-DIBCO 2018
Connection Reduction of DenseNet for Image Recognition
Baseline is a densely connected network, and the networks connected by the two new algorithms are named ShortNet1 and ShortNet2 respectively.
Ranked #3 on
Image Classification
on SVHN
(Percentage correct metric)
Efficient Convolutional Neural Networks on Raspberry Pi for Image Classification
However, due to the limitation of computing power, deep learning algorithms are usually not available on mobile devices.
Ranked #4 on
Image Classification
on SVHN
(Percentage correct metric)
Aggregated Pyramid Vision Transformer: Split-transform-merge Strategy for Image Recognition without Convolutions
This proves that Transformer has a good prospect in the field of image recognition.
Ranked #9 on
Image Classification
on CIFAR-10
(Parameters metric)
ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
However, this compression method may result in a decrease in the model accuracy and an increase in the parameters and model size.
Ranked #5 on
Image Classification
on SVHN
(Percentage correct metric)
New Pruning Method Based on DenseNet Network for Image Classification
This work employs this method to connect blocks of different depths in different ways to reduce the usage of memory.
Ranked #10 on
Image Classification
on CIFAR-10
(Accuracy metric)
