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Structure-Preserving Histopathological Stain Normalization via Attention-Guided Residual Learning [PDF]

Bioengineering
Staining variability in histopathological images compromises automated diagnostic systems by affecting the reliability of computational pathology algorithms.
Nuwan Madusanka, Prathiksha Padmanabha, Kasunika Guruge, Byeong-il Lee   +3 more
doaj   +2 more sources

Stable polyp-scene classification via subsampling and residual learning from an imbalanced large dataset [PDF]

Healthcare Technology Letters, 2019
This Letter presents a stable polyp-scene classification method with low false positive (FP) detection. Precise automated polyp detection during colonoscopies is essential for preventing colon-cancer deaths.
Hayato Itoh, Holger Roth, Holger Roth, Masahiro Oda, Masashi Misawa, Masashi Misawa, Yuichi Mori, Shin-Ei Kudo, Kensaku Mori   +8 more
doaj   +2 more sources

Gait Recognition With Wearable Sensors Using Modified Residual Block-Based Lightweight CNN

IEEE Access, 2022
Gait recognition with wearable sensors is an effective approach to identifying people by recognizing their distinctive walking patterns. Deep learning-based networks have recently emerged as a promising technique in gait recognition, yielding better ...
Md. Al Mehedi Hasan, Fuad Al Abir, Md. Al Siam, Jungpil Shin   +3 more
doaj   +1 more source

Dog Nose-Print Identification Using Deep Neural Networks

IEEE Access, 2021
Recently, there has been rapid growth in the number of people who own companion pets (cats and dogs) due to low birth rates, an increasingly aging population, and an increasing number of single-person households.
Han Byeol Bae, Daehyun Pak, Sangyoun Lee
doaj   +1 more source

MRU-NET: A U-Shaped Network for Retinal Vessel Segmentation

Applied Sciences, 2020
Fundus blood vessel image segmentation plays an important role in the diagnosis and treatment of diseases and is the basis of computer-aided diagnosis.
Hongwei Ding, Xiaohui Cui, Leiyang Chen, Kun Zhao   +3 more
doaj   +1 more source

Layer Decomposition Learning Based on Gaussian Convolution Model and Residual Deblurring for Inverse Halftoning

Applied Sciences, 2021
Layer decomposition to separate an input image into base and detail layers has been steadily used for image restoration. Existing residual networks based on an additive model require residual layers with a small output range for fast convergence and ...
Chang-Hwan Son
doaj   +1 more source

Hyperspectral Image Denoising via Adversarial Learning

Remote Sensing, 2022
Due to sensor instability and atmospheric interference, hyperspectral images (HSIs) often suffer from different kinds of noise which degrade the performance of downstream tasks.
Junjie Zhang, Zhouyin Cai, Fansheng Chen, Dan Zeng   +3 more
doaj   +1 more source

Daily Peak-Electricity-Demand Forecasting Based on Residual Long Short-Term Network

Mathematics, 2022
Forecasting the electricity demand of buildings is a key step in preventing a high concentration of electricity demand and optimizing the operation of national power systems.
Hyunsoo Kim, Jiseok Jeong, Changwan Kim
doaj   +1 more source

Underwater Image Enhancement via Triple-Branch Dense Block and Generative Adversarial Network

Journal of Marine Science and Engineering, 2023
The complex underwater environment and light scattering effect lead to severe degradation problems in underwater images, such as color distortion, noise interference, and loss of details.
Peng Yang, Chunhua He, Shaojuan Luo, Tao Wang, Heng Wu   +4 more
doaj   +1 more source

Depth Map Super-Resolution Reconstruction Based on Multi-Channel Progressive Attention Fusion Network

Applied Sciences, 2023
Depth maps captured by traditional consumer-grade depth cameras are often noisy and low-resolution. Especially when upsampling low-resolution depth maps with large upsampling factors, the resulting depth maps tend to suffer from vague edges.
Jiachen Wang, Qingjiu Huang
doaj   +1 more source