Results 51 to 60 of about 1,341,334 (344)
Enhanced CNN for image denoising [PDF]
CAAI Transactions on Intelligence Technology, 2019 Owing to the flexible architectures of deep convolutional neural networks (CNNs) are successfully used for image denoising. However, they suffer from the following drawbacks: (i) deep network architecture is very difficult to train. (ii) Deeper networks face the challenge of performance saturation.
Lunke Fei +5 more
openaire +3 more sources
Image enhancement using fuzzy intensity measure and adaptive clipping histogram equalization [PDF]
, 2019 Image enhancement aims at processing an input image so that the visual content of the output image is more pleasing or more useful for certain applications. Although histogram equalization is widely used in image enhancement due to its simplicity and
Tany, Jin +4 more
core
FoxO1 signaling in B cell malignancies and its therapeutic targeting
FEBS Letters, EarlyView.FoxO1 has context‐specific tumor suppressor or oncogenic character in myeloid and B cell malignancies. This includes tumor‐promoting properties such as stemness maintenance and DNA damage tolerance in acute leukemias, or regulation of cell proliferation and survival, or migration in mature B cell malignancies.
Krystof Hlavac +3 more
wiley +1 more source
Underwater Image Enhancement Using Convolutional Neural Network [PDF]
arXiv, 2021 This work proposes a method for underwater image enhancement using the principle of histogram equalization. Since underwater images have a global strong dominant colour, their colourfulness and contrast are often degraded. Before applying the histogram equalisation technique on the image, the image is converted from coloured image to a gray scale image
arxiv
Insights into PI3K/AKT signaling in B cell development and chronic lymphocytic leukemia
FEBS Letters, EarlyView.This Review explores how the phosphoinositide 3‐kinase and protein kinase B pathway shapes B cell development and drives chronic lymphocytic leukemia, a common blood cancer. It examines how signaling levels affect disease progression, addresses treatment challenges, and introduces novel experimental strategies to improve therapies and patient outcomes.
Maike Buchner
wiley +1 more source
The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement [PDF]
arXiv, 2022 There is an increasing consensus that the design and optimization of low light image enhancement methods need to be fully driven by perceptual quality. With numerous approaches proposed to enhance low-light images, much less work has been dedicated to quality assessment and quality optimization of low-light enhancement.
arxiv
Image-Enhanced Endoscopy in Practice [PDF]
Canadian Journal of Gastroenterology, 2009 The detection, diagnosis and treatment of early cancers offers the best hope for the prevention and cure of gastrointestinal cancers – one of the leading causes of death worldwide (1). The detection of pre- or early cancer using white light endoscopy can be challenging because their morphology can be inconspicuous (ie, nonpolypoid; slightly elevated ...
Roy Soetikno +2 more
openaire +4 more sources
FEBS Letters, EarlyView.Low‐density lipoprotein receptor‐related protein 6 (LRP6) is a key receptor for the Wnt antagonist Dickkopf1 (DKK1). DKK1 protein expression is induced in a bleomycin (BLM)‐induced lung injury model. We show that DKK1 induces proinflammatory and profibrotic genes in lung fibroblasts.
Eun‐Ah Sung +6 more
wiley +1 more source
Choosing the Optimal Spatial Domain Measure of Enhancement for Mammogram Images
International Journal of Biomedical Imaging, 2014 Medical imaging systems often require image enhancement, such as improving the image contrast, to provide medical professionals with the best visual image quality. This helps in anomaly detection and diagnosis.
Karen Panetta, Arash Samani, Sos Agaian
doaj +1 more source
DILIE: Deep Internal Learning for Image Enhancement [PDF]
arXiv, 2020 We consider the generic deep image enhancement problem where an input image is transformed into a perceptually better-looking image. Recent methods for image enhancement consider the problem by performing style transfer and image restoration. The methods mostly fall into two categories: training data-based and training data-independent (deep internal ...
arxiv