Sökning: "CLAHE"
Visar resultat 1 - 5 av 10 uppsatser innehållade ordet CLAHE.
1. Cell Identification from Microscopy Images using Deep Learning on Automatically Labeled Data
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : In biology, cell counting provides a fundamental metric for live-cell experiments. Unfortunately, most researchers are constrained to using tedious and invasive methods for counting cells. Automatic identification of cells in microscopy images would therefore be a valuable tool for such researchers. LÄS MER
2. Marine Habitat Mapping Using Image Enhancement Techniques & Machine Learning
Master-uppsats, Jönköping University/JTH, Avdelningen för datateknik och informatikSammanfattning : AbstractThe mapping of habitats is the first step that is done in policies that target theenvironment, as well as in spatial planning and management. The biodiversityplans are always centered around habitats. Therefore, constant monitoring ofthese delicate species in terms of health, changes, and extinction is a must inbiodiversity plans. LÄS MER
3. Image enhancement effect on the performance of convolutional neural networks
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Context. Image enhancement algorithms can be used to enhance the visual effects of images in the field of human vision. So can image enhancement algorithms be used in the field of computer vision? The convolutional neural network, as the most powerful image classifier at present, has excellent performance in the field of image recognition. LÄS MER
4. Image Enhancement & Automatic Detection of Exudates in Diabetic Retinopathy
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för tillämpad signalbehandlingSammanfattning : Diabetic retinopathy (DR) is becoming a global health concern, which causes the loss of vision of most patients with the disease. Due to the vast prevalence of the disease, the automated detection of the DR is needed for quick diagnoses where the progress of the disease is monitored by detection of exudates changes and their classifications in the fundus retina images. LÄS MER
5. An evaluation of image preprocessing for classification of Malaria parasitization using convolutional neural networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this study, the impact of multiple image preprocessing methods on Convolutional Neural Networks (CNN) was studied. Metrics such as accuracy, precision, recall and F1-score (Hossin et al. 2011) were evaluated. Specifically, this study is geared towards malaria classification using the data set made available by the U. LÄS MER