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Improving Performance of Biomedical Information Retrieval using Document-Level Field Boosting and BM25F Weighting
(Master thesis, 2010)Corpora of biomedical information typically contains large amounts of ambiguous data, as proteins and genes can be referred to by a number of different terms, making information retrieval difficult. This thesis investigates ... -
Improving Performance of Biomedical Retrieval using Expectation Maximization
(Master thesis, 2011)I denne oppgaven skal du implementere et statistisk metode for å forbedre et søkeresultat. Du skal bruke Expetcation-Maximization (EM) metode til formålet. Oppgaven går ut på å finne ut hvor nyttig EM til å resortere et ... -
Improving Query Processing Performance in Large Distributed Database Management Systems
(Doctoral Theses at NTNU, 1503-8181; 2011:293, Doctoral thesis, 2011)The dream of computing power as readily available as the electricity in a wall socket is coming closer to reality with the arrival of grid and cloud computing. At the sametime, databases grow to sizes beyond what can be ... -
Improving real-time human pose estimation from multi-view video
(Doktoravhandlinger ved NTNU, 1503-8181; 2013:150, Doctoral thesis, 2013)Capturing human motion is a key problem in computer vision, because of the wide range of applications that can benefit from the acquired data. Motion capture is used to identify people by their gait, for interacting with ... -
Improving recommender systems with machine learning and social media
(Master thesis, 2017)This thesis studies the opportunity to utilize posts from social media in recommender systems. Recommender systems are used to help users find content they are interested in when there are many alternatives, and is very ... -
Improving reproducibility of artificial intelligence research to increase trust and productivity
(Chapter, 2023)Several recent studies have shown that many scientific results cannot be trusted. While the “reproducibility crisis” was first recognised in psychology, the problem affects most if not all branches of science. This essay ... -
Improving RRB-Tree Performance through Transience
(Master thesis, 2014)The RRB-tree is a confluently persistent data structure based on the persistent vector, with efficient concatenation and slicing, and effectively constant time indexing, updates and iteration. Although efficient appends ... -
Improving Search in Social Media Images with External Information
(Master thesis, 2014)The use of social media has increased considerably the recent years, andusers share a lot of their daily life in social media. Many of the users uploadimages to photo-sharing applications, and categorize their images ... -
Improving Security and Safety Co-analysis of STPA
(Chapter, 2019)Many safety and security co-analysis methods have been proposed to assure the safety of critical systems, including autonomous systems. One example of safety and security co-analysis approach is Systems-Theoretic Process ... -
Improving sliding-block puzzle solving using meta-level reasoning
(Master thesis, 2010)In this thesis, we develop a meta-reasoning system based on CBR which solves sliding-block puzzles. The meta-reasoning system is built on top of a search-based sliding-block puzzle solving program which was developed as ... -
Improving Spatial Data Processing by Clipping Minimum Bounding Boxes
(Chapter, 2018)The majority of spatial processing techniques rely heavily on the idea of approximating each group of spatial objects by their minimum bounding box (MBB). As each MBB is compact to store (requiring only two multi-dimensional ... -
Improving System Usability of Climbing Mont Blanc - An Online Judge for Energy Efficient Programming
(Master thesis, 2016)For each release of a new smartphone model, the limits of their CPUs, so called heterogeneous multicore processors, are pushed. As a result, the usage of such processors has gained an increased interest outside the mobile ... -
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise
(Peer reviewed; Journal article, 2022)Q-learning is one of the most well-known Reinforcement Learning algorithms. There have been tremendous efforts to develop this algorithm using neural networks. Bootstrapped Deep Q-Learning Network is amongst them. It ... -
Improving the Energy-Efficiency of Task Based Programming on Chip Multiprocessors
(Doctoral theses at NTNU, 2017:175, Doctoral thesis, 2017)In the early 2000s, the superscalar CPU paradigm reached the point of diminishing returns mainly due to power requirements and overheating concerns. Faced with a constant demand for performance, hardware developers were ... -
Improving the first-level cache bandwidth in the Berkeley Out-of-Order Machine
(Master thesis, 2023)Ettersom moderne prosessorer de siste tiårene har truffet minnegapet, har de brukt minne-nivå-parallelisme(MLP) for skjule forskjellen i ytelse mellom prosessoren og minnet. For å utnytte MLP trenger prosessorer nok ... -
Improving the Performance of Parallel Applications in Chip Multiprocessors with Architectural Techniques
(Master thesis, 2007)Chip Multiprocessors (CMPs) or multi-core architectures are a new class of processor architectures. Here, multiple processing cores are placed on the same physical chip. To reach the performance potential of these architectures ... -
Improving the Performance of Pipelined Query Processing with Skipping
(Journal article; Peer reviewed, 2012)Web search engines need to provide high throughput and short query latency. Recent results show that pipelined query processing over a term-wise partitioned inverted index may have superior throughput. However, the query ... -
Improving the Performance of Processor Core Simulation in the M5 Simulator
(Master thesis, 2008)Simulators are often used to evaluate new ideas in computer architecture research. Unfortunately, detailed simulation is computationally expensive, leading to long simulation turn-around times. This is particularly true ... -
Improving the robustness of neural networks for time series forecasting through augmentationswith specific characteristics
(Master thesis, 2021)Nevrale nettverk er sett på som en toppmoderne metode i mange oppgaver som handler om mønstergjenkjenning, som bildeklassifisering og maskinoversettelse. Likevel har det blitt vist nevrale nettverk ofte produserer prediksjoner ... -
Improving the semantic segmentation of historical aerial images of riverscapes using both data-centric and model-centric approaches.
(Master thesis, 2022)Menneskelig utbygging legger press på elvelandskapet, noe som setter bevaring av landområder og biologisk mangfold i en farlig situasjon. For å vurdere endringene og undersøke restaureringspotensialet, er det viktig å ...