Blar i NTNU Open på forfatter "Misimi, Ekrem"
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A Deep Learning-Based 3D Vision Pipeline for Shape Completion of 3D Objects
Kongsgård, Sondre Bø (Master thesis, 2019)Enkelt-vis formfullføring omhandler problemet hvor målet er å estimere den komplette geometrien fra delvise observasjoner av objekter, noe som er essensielt i mange applikasjoner innen datasyn og robotikk. Denne oppgaven ... -
A Dual-Stream Deep Learning Architecture for Action Recognition in Salmon from Underwater Video.
Måløy, Håkon (Master thesis, 2017)Over half of the costs from breeding salmon in the Norwegian salmon farming industry comes from feed usage. Today the feeding process is largely a manual labor, requiring an operator to monitor the amount of feed sinking ... -
A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture
Måløy, Håkon; Aamodt, Agnar; Misimi, Ekrem (Journal article; Peer reviewed, 2019)Recent developments have shown that Deep Learning approaches are well suited for Human Action Recognition. On the other hand, the application of deep learning for action or behaviour recognition in other domains such as ... -
Computer vision for quality grading in fish processing
Misimi, Ekrem (Doktoravhandlinger ved NTNU, 1503-8181; 2007:244, Doctoral thesis, 2007)High labour costs, due to the existing technology that still involves a high degree of manually based processing, incur overall high production costs in the fish processing industry. Therefore, a higher degree of automation ... -
Deep Reinforcement Learning for Gripper Vector Estimation
Olsen, Thomas; Ottesen, Birk Midtbø (Master thesis, 2018)The problem of gripper vector estimation, also referred to as gripper pose estimation, is the problem of constructing a vector describing the pose of the end-effector of a robotic gripper, which enables it to grasp an ... -
Fast and accurate GPU accelerated, high resolution 3D registration for robotic 3D reconstruction of compliant Food objects
Isachsen, Ulrich Johan; Theoharis, Theoharis; Misimi, Ekrem (Peer reviewed; Journal article, 2020)If we are to develop robust robot-based automation in primary production and processing in the agriculture and ocean space sectors, we have to develop solid vision-based perception for the robots. Accurate vision-based ... -
Gradual Reduction in Sodium Content in Cooked Ham, with Corresponding Change in Sensorial Properties Measured by Sensory Evaluation and a Multimodal Machine Vision System
Greiff, Kirsti; Mathiassen, John Reidar Bartle; Misimi, Ekrem; Hersleth, Margrethe; Aursand, Ida Grong (Journal article; Peer reviewed, 2015)The European diet today generally contains too much sodium (Na+). A partial substitution of NaCl by KCl has shown to be a promising method for reducing sodium content. The aim of this work was to investigate the sensorial ... -
iPROCESS innovation - Innovative and Flexible Food Processing Technology in Norway - 2020:00981 A
Krupa, Alexandre; Andersen, Petter Vejle; Wold, Jens Petter; Thakur, Maitri; Verboven, Pieter; Lind, Morten; Dreyer, Heidi Carin; Vatn, Jørn; Tveterås, Ragnar; Sandvold, Hilde Ness (Research report, 2020)To develop novel concepts and methods for flexible and sustainable food processing in Norway with the aim of coping with small volume series and high biological variation in existing raw materials, to enable increased raw ... -
Learning neural representations for the processing of temporal data in deep neutral networks
Måløy, Håkon (Doctoral theses at NTNU;2023:6, Doctoral thesis, 2023)Ever since the third spring of artificial intelligence a decadeago, representation learning through deep neural networks hasbeen the dominating approach for most research in machinelearning. However, typical deep neural ... -
Real-time point cloud registration from RGB-D camera mounted on a robot arm using GPU acceleration
Isachsen, Ulrich Johan (Master thesis, 2018)Recent development of 3D scanners have provided small, precise and cheap consumer grade scanners operating in real-time. Especially because of their low weight, they are being considered for usage in visual servoing (vision ... -
Robust Classification Approaches to Industrial Sorting of Herring Fractions
Guttormsen, Erik (Master thesis, 2015)Among the rest raw material produced during the filleting process of herring there are high value products such as roe and milt. As of today there has been little or no major effort to process these by-products at an ... -
Single-View 3D Shape Completion for Robotic Grasping of Objects via Deep Neural Fields
Sundt, Peder Bergebakken (Master thesis, 2021)Vi undersøker i denne oppgaven rekonstruksjon av fullstendige volumetriske 3D modeller fra et enkelt synspunkt, for å gi en robotarm utstyrt med 3D syn ferdigheten til å antyde fasongen til objekter og derav håndtere dem. ... -
SLCP: Stochastic Latent Consistency Policy for closed-loop 6-DOF Grasping
Monsen, Øyvind (Master thesis, 2024)#import "/chapters/5 - exp and result.typ": as_perc, perf_overall, perf_seen En viktig oppgave i robotmanipulering er 6-DOF (6 frihetsgrader) griping. Mange av de tidligere løsningene på dette problemet var basert på ... -
Tactile-sensitive robotic grasping of food compliant objects with deep learning as a learning policy
Olofsson, Alexander Martin (Master thesis, 2017)This thesis outlines work done in generating models used to control a robotic arm and tactile sensitive gripper for successfully grasping compliant food objects, using colour and depth images as input. The compliant food ... -
Towards automated sorting of Atlantic cod (Gadus morhua) roe, milt, and liver - Spectral characterization and classification using visible and near-infrared hyperspectral imaging
Paluchowski, Lukasz A.; Misimi, Ekrem; Grimsmo, Leif; Randeberg, Lise Lyngsnes (Journal article; Peer reviewed, 2016)Technological solutions regarding automated sorting of food according to their quality parameters are of great interest to food industry. In this regard, automated sorting of fish rest raw materials remains as one of the ... -
Understanding and Visualizing Filters in Deep Convolutional Neural Network Architectures
Aunrønning, Ola (Master thesis, 2018)Deep neural networks are black boxes. While we know how they learn, we still don t have a great understanding of what they learn. This project has a goal of visualizing and understanding what convolutional neural networks ...