Essays about: "Peak signal to noise ratio"

Showing result 1 - 5 of 38 essays containing the words Peak signal to noise ratio.

1. 1. Analyzing the Influence of Synthetic andAugmented Data on Segmentation Model

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Alex Peschel; [2023]
   Keywords : Artificial Intelligence; Microorganisms; Segmentation; Synthesizing; Augmentation;

   Abstract : The field of Artificial Intelligence (AI) has experienced unprecedented growth in recent years, thanks to the numerous applications related to speech recognition, natural language processing, and computer vision. However, one of the challenges facing AI is the requirement for large amounts of energy, time, and data to be effective and accurate. READ MORE

3. 2. Digital Front End Algorithms for Sub-Band Full Duplex

   University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

   Author : Midhat Rizvi; Khaled Al-Khateeb; [2023]
   Keywords : Adjacent Channel Leakage Ratio; Bit Error Rate; Clipping and Filtering; Crest Factor Reduction; Digital front end; Digital Pre-Distortion Error Vector Magnitude; Frequency Division Duplex; Power Amplifier; Peak to Average Power Ratio; Peak Cancellation Crest Factor Reduction; Sub Band Full Duplex; Self-Interference Cancellation; Signal-to-Interference Noise Ratio; Signal-to-Noise Ratio; Turbo Clipping; Time Division Duplex; Technology and Engineering;

   Abstract : Sub-band full duplex is a new communication scheme technology, where a single frequency band is partitioned into sub-bands for downlink (DL) and up-link(UL) transmissions, and both can take place simultaneously. The idea behind the sub-band full duplex development is to improve the throughput, and coverage and reduce the latency of the UL communication by allowing the UL reception during the DL transmission. READ MORE

4. 3. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

   University essay from Linköpings universitet/Institutionen för medicinsk teknik

   Author : William Tirmén; [2023]
   Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

   Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE

5. 4. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction

   University essay from KTH/Matematisk statistik

   Author : Sabina Syed; Josefin Stenberg; [2023]
   Keywords : Adversarial Convex Regularization; Computer Vision; Cone Beam Computed Tomography; Convolutional Neural Networks; Deep Learning; Image Reconstruction; Adversarial Convex Regularization; Bildrekonstruktion; Datorseende; Djupinlärning; Faltningsnätverk; Volymtomografi;

   Abstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE

6. 5. Real-Time Video Super-Resolution : A Comparative Study of Interpolation and Deep Learning Approaches to Upsampling Real-Time Video

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Erik Båvenstrand; [2021]
   Keywords : Super-Resolution; Real-Time; Deep Learning; Upsampling; Computer Vision; Machine Learning; Motion Compensation; Temporal Coherence; Superupplösning; Realtid; Djupinlärning; Uppsampling; Datorseende; Maskininlärning; Rörelsekompensation; Temporalt Sammanhängande;

   Abstract : Super-resolution is a subfield of computer vision centered around upsampling low-resolution images to a corresponding high-resolution counterpart. This degree project investigates the suitability of a deep learning method for real-time video super-resolution. READ MORE